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<div class="section" id="seldon-package">
<h1>seldon package<a class="headerlink" href="#seldon-package" title="Permalink to this headline">¶</a></h1>
<div class="section" id="subpackages">
<h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to this headline">¶</a></h2>
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<li class="toctree-l1"><a class="reference internal" href="seldon.anomaly.html">seldon.anomaly package</a><ul>
<li class="toctree-l2"><a class="reference internal" href="seldon.anomaly.html#submodules">Submodules</a></li>
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<li class="toctree-l1"><a class="reference internal" href="seldon.cli.html">seldon.cli package</a><ul>
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<li class="toctree-l2"><a class="reference internal" href="seldon.cli.html#module-seldon.cli.attr_schema_utils">seldon.cli.schema_utils</a></li>
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<li class="toctree-l2"><a class="reference internal" href="seldon.pipeline.html#module-seldon.pipeline.auto_transforms">seldon.pipeline.auto_transforms module</a></li>
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<li class="toctree-l2"><a class="reference internal" href="seldon.pipeline.html#seldon-pipeline-bayes-optimize-module">seldon.pipeline.bayes_optimize module</a></li>
<li class="toctree-l2"><a class="reference internal" href="seldon.pipeline.html#module-seldon.pipeline.cross_validation">seldon.pipeline.cross_validation module</a></li>
<li class="toctree-l2"><a class="reference internal" href="seldon.pipeline.html#module-seldon.pipeline.pandas_pipelines">seldon.pipeline.pandas_pipelines module</a></li>
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<div class="section" id="submodules">
<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline">¶</a></h2>
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<div class="section" id="module-seldon.fileutil">
<span id="seldon-fileutil-module"></span><h2>seldon.fileutil module<a class="headerlink" href="#module-seldon.fileutil" title="Permalink to this headline">¶</a></h2>
<dl class="class">
<dt id="seldon.fileutil.FileUtil">
<em class="property">class </em><code class="descclassname">seldon.fileutil.</code><code class="descname">FileUtil</code><span class="sig-paren">(</span><em>aws_key=None</em>, <em>aws_secret=None</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/fileutil.html#FileUtil"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.fileutil.FileUtil" title="Permalink to this definition">¶</a></dt>
<dd><p>utilities to input and output files. Locally or from AWS S3.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>[Optional</strong> (<em>secret</em>) – aws key</li>
<li><strong>[Optional</strong> – aws secret</li>
</ul>
</td>
</tr>
</tbody>
</table>
<dl class="method">
<dt id="seldon.fileutil.FileUtil.copy">
<code class="descname">copy</code><span class="sig-paren">(</span><em>fromPath</em>, <em>toPath</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/fileutil.html#FileUtil.copy"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.fileutil.FileUtil.copy" title="Permalink to this definition">¶</a></dt>
<dd><p>copy files. local->local, S3->local, local->S3 (S3->S3 not supported)</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>fromPath</strong> (<em>str</em>) – local or S3 URL</li>
<li><strong>toPath</strong> (<em>str</em>) – local or S3 URL</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="seldon.fileutil.FileUtil.copy_local">
<code class="descname">copy_local</code><span class="sig-paren">(</span><em>fromPath</em>, <em>toPath</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/fileutil.html#FileUtil.copy_local"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.fileutil.FileUtil.copy_local" title="Permalink to this definition">¶</a></dt>
<dd><p>copy local folders</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>fromPath</strong> (<em>str</em>) – local from path to copy all files under</li>
<li><strong>toPath</strong> (<em>str</em>) – local destination folder (will be created if does not exist)</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="seldon.fileutil.FileUtil.copy_s3_file">
<code class="descname">copy_s3_file</code><span class="sig-paren">(</span><em>fromPath</em>, <em>bucket</em>, <em>path</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/fileutil.html#FileUtil.copy_s3_file"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.fileutil.FileUtil.copy_s3_file" title="Permalink to this definition">¶</a></dt>
<dd><p>copy from local file to S3</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>fromPath</strong> (<em>str</em>) – local file</li>
<li><strong>bucket</strong> (<em>str</em>) – S3 bucket</li>
<li><strong>path</strong> (<em>str</em>) – S3 prefix to add to files</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="seldon.fileutil.FileUtil.download_s3">
<code class="descname">download_s3</code><span class="sig-paren">(</span><em>fromPath</em>, <em>toPath</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/fileutil.html#FileUtil.download_s3"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.fileutil.FileUtil.download_s3" title="Permalink to this definition">¶</a></dt>
<dd><p>download from S3 to local folder</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>fromPath</strong> (<em>str</em>) – S3 URL</li>
<li><strong>toPath</strong> (<em>str</em>) – local folder</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="seldon.fileutil.FileUtil.stream">
<code class="descname">stream</code><span class="sig-paren">(</span><em>inputPath</em>, <em>fn</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/fileutil.html#FileUtil.stream"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.fileutil.FileUtil.stream" title="Permalink to this definition">¶</a></dt>
<dd><p>stream from an inputpath calling function</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>inputPath</strong> (<em>str</em>) – input path to stream from</li>
<li><strong>fn</strong> (<em>function</em>) – function to call</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="seldon.fileutil.FileUtil.stream_decompress">
<code class="descname">stream_decompress</code><span class="sig-paren">(</span><em>stream</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/fileutil.html#FileUtil.stream_decompress"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.fileutil.FileUtil.stream_decompress" title="Permalink to this definition">¶</a></dt>
<dd><p>decompress a stream</p>
</dd></dl>
<dl class="method">
<dt id="seldon.fileutil.FileUtil.stream_gzip">
<code class="descname">stream_gzip</code><span class="sig-paren">(</span><em>k</em>, <em>fn</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/fileutil.html#FileUtil.stream_gzip"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.fileutil.FileUtil.stream_gzip" title="Permalink to this definition">¶</a></dt>
<dd><p>stream from gzip file and call function for each line</p>
<table class="docutils field-list" frame="void" rules="none">
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<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>k</strong> (<em>file</em>) – input gziped file</li>
<li><strong>fn</strong> (<em>function</em>) – function to call for each line</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="seldon.fileutil.FileUtil.stream_multi">
<code class="descname">stream_multi</code><span class="sig-paren">(</span><em>inputPaths</em>, <em>fn</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/fileutil.html#FileUtil.stream_multi"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.fileutil.FileUtil.stream_multi" title="Permalink to this definition">¶</a></dt>
<dd><p>stream multilple paths calling a function on each line</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>inputPaths</strong> (<em>list</em>) – list of input folders</li>
<li><strong>fn</strong> (<em>function</em>) – function to call</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="seldon.fileutil.FileUtil.stream_other">
<code class="descname">stream_other</code><span class="sig-paren">(</span><em>path</em>, <em>fn</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/fileutil.html#FileUtil.stream_other"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.fileutil.FileUtil.stream_other" title="Permalink to this definition">¶</a></dt>
<dd><p>stream from local folders call a function</p>
<table class="docutils field-list" frame="void" rules="none">
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<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>folders</strong> (<em>list</em>) – list of folders</li>
<li><strong>fn</strong> (<em>function</em>) – function to call</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="seldon.fileutil.FileUtil.stream_s3">
<code class="descname">stream_s3</code><span class="sig-paren">(</span><em>bucket</em>, <em>prefix</em>, <em>fn</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/fileutil.html#FileUtil.stream_s3"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.fileutil.FileUtil.stream_s3" title="Permalink to this definition">¶</a></dt>
<dd><p>stream from an AWS S3 bucket all files under a prefix and call a function</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>bucket</strong> (<em>str</em>) – name of S3 bucket</li>
<li><strong>prefix</strong> (<em>str</em>) – prefix in bucket</li>
<li><strong>fn</strong> (<em>function</em>) – function to call for each line</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="seldon.fileutil.FileUtil.upload_s3">
<code class="descname">upload_s3</code><span class="sig-paren">(</span><em>fromPath</em>, <em>toPath</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/fileutil.html#FileUtil.upload_s3"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.fileutil.FileUtil.upload_s3" title="Permalink to this definition">¶</a></dt>
<dd><p>upload from local path to S3</p>
<table class="docutils field-list" frame="void" rules="none">
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<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>fromPath</strong> (<em>str</em>) – folder to copy from</li>
<li><strong>toPath</strong> (<em>str</em>) – S3 URL</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
</div>
<div class="section" id="module-seldon.keras">
<span id="seldon-keras-module"></span><h2>seldon.keras module<a class="headerlink" href="#module-seldon.keras" title="Permalink to this headline">¶</a></h2>
<dl class="class">
<dt id="seldon.keras.KerasClassifier">
<em class="property">class </em><code class="descclassname">seldon.keras.</code><code class="descname">KerasClassifier</code><span class="sig-paren">(</span><em>model_create=<function default_classification_model></em>, <em>tmp_model='/tmp/model'</em>, <em>target=None</em>, <em>target_readable=None</em>, <em>included=None</em>, <em>excluded=None</em>, <em>id_map={}</em>, <em>optimizer='adam'</em>, <em>loss='categorical_crossentropy'</em>, <em>train_batch_size=128</em>, <em>test_batch_size=128</em>, <em>nb_epoch=100</em>, <em>shuffle=True</em>, <em>show_accuracy=False</em>, <em>validation_split=0</em>, <em>validation_data=None</em>, <em>callbacks=None</em>, <em>verbose=0</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/keras.html#KerasClassifier"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.keras.KerasClassifier" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="seldon.pipeline.html#seldon.pipeline.pandas_pipelines.BasePandasEstimator" title="seldon.pipeline.pandas_pipelines.BasePandasEstimator"><code class="xref py py-class docutils literal"><span class="pre">seldon.pipeline.pandas_pipelines.BasePandasEstimator</span></code></a>, <code class="xref py py-class docutils literal"><span class="pre">sklearn.base.BaseEstimator</span></code>, <code class="xref py py-class docutils literal"><span class="pre">sklearn.base.ClassifierMixin</span></code></p>
<dl class="method">
<dt id="seldon.keras.KerasClassifier.__getstate__">
<code class="descname">__getstate__</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/keras.html#KerasClassifier.__getstate__"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.keras.KerasClassifier.__getstate__" title="Permalink to this definition">¶</a></dt>
<dd><p>Remove parts of class that cause issue in pickling. Can recreate them in setstate</p>
</dd></dl>
<dl class="method">
<dt id="seldon.keras.KerasClassifier.__setstate__">
<code class="descname">__setstate__</code><span class="sig-paren">(</span><em>dict</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/keras.html#KerasClassifier.__setstate__"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.keras.KerasClassifier.__setstate__" title="Permalink to this definition">¶</a></dt>
<dd><p>Create compiled model from parameters. saving model to file and loading it back in</p>
</dd></dl>
<dl class="method">
<dt id="seldon.keras.KerasClassifier.fit">
<code class="descname">fit</code><span class="sig-paren">(</span><em>X</em>, <em>y=None</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/keras.html#KerasClassifier.fit"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.keras.KerasClassifier.fit" title="Permalink to this definition">¶</a></dt>
<dd><p>Derived from <a class="reference external" href="https://github.com/fchollet/keras/blob/master/keras/wrappers/scikit_learn.py">https://github.com/fchollet/keras/blob/master/keras/wrappers/scikit_learn.py</a>
Adds:
Handling pandas inputs
Saving of model into the class to allow for easy pickling</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>X</strong> (<em>pandas dataframe or array-like</em>) – training samples</li>
<li><strong>y</strong> (<em>array like, required for array-like X and not used presently for pandas dataframe</em>) – class labels</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first"><strong>self</strong></p>
</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">object</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="seldon.keras.KerasClassifier.predict_proba">
<code class="descname">predict_proba</code><span class="sig-paren">(</span><em>X</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/keras.html#KerasClassifier.predict_proba"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.keras.KerasClassifier.predict_proba" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns class probability estimates for the given test data.</p>
<dl class="docutils">
<dt>X <span class="classifier-delimiter">:</span> <span class="classifier">pandas dataframe or array-like</span></dt>
<dd>Test samples</dd>
</dl>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body"><strong>proba</strong> –
Class probability estimates.</td>
</tr>
<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">array-like, shape = (n_samples, n_outputs)</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
<dl class="function">
<dt id="seldon.keras.default_classification_model">
<code class="descclassname">seldon.keras.</code><code class="descname">default_classification_model</code><span class="sig-paren">(</span><em>input_width</em>, <em>num_classes</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/keras.html#default_classification_model"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.keras.default_classification_model" title="Permalink to this definition">¶</a></dt>
<dd><p>Default classification model</p>
</dd></dl>
</div>
<div class="section" id="module-seldon.sklearn_estimator">
<span id="seldon-sklearn-estimator-module"></span><h2>seldon.sklearn_estimator module<a class="headerlink" href="#module-seldon.sklearn_estimator" title="Permalink to this headline">¶</a></h2>
<dl class="class">
<dt id="seldon.sklearn_estimator.SKLearnClassifier">
<em class="property">class </em><code class="descclassname">seldon.sklearn_estimator.</code><code class="descname">SKLearnClassifier</code><span class="sig-paren">(</span><em>clf=None</em>, <em>target=None</em>, <em>target_readable=None</em>, <em>included=None</em>, <em>excluded=None</em>, <em>id_map={}</em>, <em>vectorizer=None</em>, <em>**sk_args</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/sklearn_estimator.html#SKLearnClassifier"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.sklearn_estimator.SKLearnClassifier" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="seldon.pipeline.html#seldon.pipeline.pandas_pipelines.BasePandasEstimator" title="seldon.pipeline.pandas_pipelines.BasePandasEstimator"><code class="xref py py-class docutils literal"><span class="pre">seldon.pipeline.pandas_pipelines.BasePandasEstimator</span></code></a>, <code class="xref py py-class docutils literal"><span class="pre">sklearn.base.BaseEstimator</span></code>, <code class="xref py py-class docutils literal"><span class="pre">sklearn.base.ClassifierMixin</span></code></p>
<p>Wrapper for XGBoost classifier with pandas support
XGBoost specific arguments follow <a class="reference external" href="https://github.com/dmlc/xgboost/blob/master/python-package/xgboost/sklearn.py">https://github.com/dmlc/xgboost/blob/master/python-package/xgboost/sklearn.py</a></p>
<dl class="docutils">
<dt>clf <span class="classifier-delimiter">:</span> <span class="classifier">sklearn estimator</span></dt>
<dd>sklearn estimator to run</dd>
<dt>target <span class="classifier-delimiter">:</span> <span class="classifier">str</span></dt>
<dd>Target column</dd>
<dt>target_readable <span class="classifier-delimiter">:</span> <span class="classifier">str</span></dt>
<dd>More descriptive version of target variable</dd>
<dt>included <span class="classifier-delimiter">:</span> <span class="classifier">list str, optional</span></dt>
<dd>columns to include</dd>
<dt>excluded <span class="classifier-delimiter">:</span> <span class="classifier">list str, optional</span></dt>
<dd>columns to exclude</dd>
<dt>id_map <span class="classifier-delimiter">:</span> <span class="classifier">dict (int,str), optional</span></dt>
<dd>map of class ids to high level names</dd>
<dt>sk_args <span class="classifier-delimiter">:</span> <span class="classifier">str, optional</span></dt>
<dd>extra args for sklearn classifier</dd>
</dl>
<dl class="method">
<dt id="seldon.sklearn_estimator.SKLearnClassifier.fit">
<code class="descname">fit</code><span class="sig-paren">(</span><em>X</em>, <em>y=None</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/sklearn_estimator.html#SKLearnClassifier.fit"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.sklearn_estimator.SKLearnClassifier.fit" title="Permalink to this definition">¶</a></dt>
<dd><p>Fit an sklearn classifier to data</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>X</strong> (<em>pandas dataframe or array-like</em>) – training samples</li>
<li><strong>y</strong> (<em>array like, required for array-like X and not used presently for pandas dataframe</em>) – class labels</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first"><strong>self</strong></p>
</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">object</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="seldon.sklearn_estimator.SKLearnClassifier.predict">
<code class="descname">predict</code><span class="sig-paren">(</span><em>X</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/sklearn_estimator.html#SKLearnClassifier.predict"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.sklearn_estimator.SKLearnClassifier.predict" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns class predictions</p>
<dl class="docutils">
<dt>X <span class="classifier-delimiter">:</span> <span class="classifier">pandas dataframe or array-like</span></dt>
<dd>Test samples</dd>
</dl>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body"><strong>proba</strong> –
Class predictions</td>
</tr>
<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">array-like, shape = (n_samples, n_outputs)</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="seldon.sklearn_estimator.SKLearnClassifier.predict_proba">
<code class="descname">predict_proba</code><span class="sig-paren">(</span><em>X</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/sklearn_estimator.html#SKLearnClassifier.predict_proba"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.sklearn_estimator.SKLearnClassifier.predict_proba" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns class probability estimates for the given test data.</p>
<dl class="docutils">
<dt>X <span class="classifier-delimiter">:</span> <span class="classifier">pandas dataframe or array-like</span></dt>
<dd>Test samples</dd>
</dl>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body"><strong>proba</strong> –
Class probability estimates.</td>
</tr>
<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">array-like, shape = (n_samples, n_outputs)</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
</div>
<div class="section" id="module-seldon.util">
<span id="seldon-util-module"></span><h2>seldon.util module<a class="headerlink" href="#module-seldon.util" title="Permalink to this headline">¶</a></h2>
<dl class="class">
<dt id="seldon.util.DeprecationHelper">
<em class="property">class </em><code class="descclassname">seldon.util.</code><code class="descname">DeprecationHelper</code><span class="sig-paren">(</span><em>new_target</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/util.html#DeprecationHelper"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.util.DeprecationHelper" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal"><span class="pre">object</span></code></p>
</dd></dl>
<dl class="class">
<dt id="seldon.util.Extension">
<em class="property">class </em><code class="descclassname">seldon.util.</code><code class="descname">Extension</code><a class="reference internal" href="modules/seldon/util.html#Extension"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.util.Extension" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal"><span class="pre">object</span></code></p>
<p>Generic function that takes dict input and return JSON</p>
<dl class="method">
<dt id="seldon.util.Extension.load">
<code class="descname">load</code><span class="sig-paren">(</span><em>folder</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/util.html#Extension.load"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.util.Extension.load" title="Permalink to this definition">¶</a></dt>
<dd><p>Load the model into the extension. Allows more complex models than can easily handled via pickling.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>folder</strong> (<em>str</em>) – local folder to load model</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="seldon.util.Extension.predict">
<code class="descname">predict</code><span class="sig-paren">(</span><em>input={}</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/util.html#Extension.predict"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.util.Extension.predict" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="seldon.util.Extension.save">
<code class="descname">save</code><span class="sig-paren">(</span><em>folder</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/util.html#Extension.save"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.util.Extension.save" title="Permalink to this definition">¶</a></dt>
<dd><p>Save the extension model. Allows more fine grained control over model state saving than pickling would allow. The method should save objects that only can’t be pickled.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>folder</strong> (<em>str</em>) – local folder to save model</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="seldon.util.ExtensionWrapper">
<em class="property">class </em><code class="descclassname">seldon.util.</code><code class="descname">ExtensionWrapper</code><span class="sig-paren">(</span><em>work_folder='/tmp'</em>, <em>aws_key=None</em>, <em>aws_secret=None</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/util.html#ExtensionWrapper"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.util.ExtensionWrapper" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal"><span class="pre">object</span></code></p>
<dl class="method">
<dt id="seldon.util.ExtensionWrapper.create_work_folder">
<code class="descname">create_work_folder</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/util.html#ExtensionWrapper.create_work_folder"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.util.ExtensionWrapper.create_work_folder" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="seldon.util.ExtensionWrapper.get_work_folder">
<code class="descname">get_work_folder</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/util.html#ExtensionWrapper.get_work_folder"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.util.ExtensionWrapper.get_work_folder" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="seldon.util.ExtensionWrapper.load_extension">
<code class="descname">load_extension</code><span class="sig-paren">(</span><em>extension_folder</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/util.html#ExtensionWrapper.load_extension"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.util.ExtensionWrapper.load_extension" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="seldon.util.ExtensionWrapper.save_extension">
<code class="descname">save_extension</code><span class="sig-paren">(</span><em>extension</em>, <em>location</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/util.html#ExtensionWrapper.save_extension"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.util.ExtensionWrapper.save_extension" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="class">
<dt id="seldon.util.Recommender">
<em class="property">class </em><code class="descclassname">seldon.util.</code><code class="descname">Recommender</code><a class="reference internal" href="modules/seldon/util.html#Recommender"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.util.Recommender" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal"><span class="pre">sklearn.base.BaseEstimator</span></code></p>
<p>General recommendation interface</p>
<dl class="method">
<dt id="seldon.util.Recommender.load">
<code class="descname">load</code><span class="sig-paren">(</span><em>folder</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/util.html#Recommender.load"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.util.Recommender.load" title="Permalink to this definition">¶</a></dt>
<dd><p>Load the model into the recommender. Allows more complex models than can easily handled via pickling.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>folder</strong> (<em>str</em>) – local folder to load model</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="seldon.util.Recommender.recommend">
<code class="descname">recommend</code><span class="sig-paren">(</span><em>user</em>, <em>ids</em>, <em>recent_interactions</em>, <em>client</em>, <em>limit</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/util.html#Recommender.recommend"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.util.Recommender.recommend" title="Permalink to this definition">¶</a></dt>
<dd><p>Recommend items</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>user</strong> (<em>long</em>) – user id</li>
<li><strong>ids</strong> (<em>list(long)</em>) – item ids to score</li>
<li><strong>recent_interactions</strong> (<em>list(long)</em>) – recent items the user has interacted with</li>
<li><strong>client</strong> (<em>str</em>) – name of client to recommend for (business group, company, product..)</li>
<li><strong>limit</strong> (<em>int</em>) – number of recommendations to return</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first"></p>
</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">list of pairs of (item_id,score)</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="seldon.util.Recommender.save">
<code class="descname">save</code><span class="sig-paren">(</span><em>folder</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/util.html#Recommender.save"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.util.Recommender.save" title="Permalink to this definition">¶</a></dt>
<dd><p>Save the recommender model. Allows more fine grained control over model state saving than pickling would allow. The method should save objects that only can’t be pickled.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>folder</strong> (<em>str</em>) – local folder to save model</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="seldon.util.RecommenderWrapper">
<em class="property">class </em><code class="descclassname">seldon.util.</code><code class="descname">RecommenderWrapper</code><span class="sig-paren">(</span><em>work_folder='/tmp'</em>, <em>aws_key=None</em>, <em>aws_secret=None</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/util.html#RecommenderWrapper"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.util.RecommenderWrapper" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal"><span class="pre">object</span></code></p>
<p>Wrapper to allow recommenders to be easily saved and loaded</p>
<dl class="method">
<dt id="seldon.util.RecommenderWrapper.create_work_folder">
<code class="descname">create_work_folder</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/util.html#RecommenderWrapper.create_work_folder"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.util.RecommenderWrapper.create_work_folder" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="seldon.util.RecommenderWrapper.get_work_folder">
<code class="descname">get_work_folder</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/util.html#RecommenderWrapper.get_work_folder"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.util.RecommenderWrapper.get_work_folder" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="seldon.util.RecommenderWrapper.load_recommender">
<code class="descname">load_recommender</code><span class="sig-paren">(</span><em>recommender_folder</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/util.html#RecommenderWrapper.load_recommender"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.util.RecommenderWrapper.load_recommender" title="Permalink to this definition">¶</a></dt>
<dd><p>Load scikit learn recommender from external folder</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>recommender_folder</strong> (<em>str</em>) – external folder holding recommender</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="seldon.util.RecommenderWrapper.save_recommender">
<code class="descname">save_recommender</code><span class="sig-paren">(</span><em>recommender</em>, <em>location</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/util.html#RecommenderWrapper.save_recommender"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.util.RecommenderWrapper.save_recommender" title="Permalink to this definition">¶</a></dt>
<dd><p>Save recommender to external location</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>recommender</strong> (<a class="reference internal" href="#seldon.util.Recommender" title="seldon.util.Recommender"><em>Recommender</em></a>) – recommender to be saved</li>
<li><strong>location</strong> (<em>str</em>) – external folder to save recommender</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
</div>
<div class="section" id="module-seldon.vw">
<span id="seldon-vw-module"></span><h2>seldon.vw module<a class="headerlink" href="#module-seldon.vw" title="Permalink to this headline">¶</a></h2>
<dl class="class">
<dt id="seldon.vw.VWClassifier">
<em class="property">class </em><code class="descclassname">seldon.vw.</code><code class="descname">VWClassifier</code><span class="sig-paren">(</span><em>target=None</em>, <em>target_readable=None</em>, <em>included=None</em>, <em>excluded=None</em>, <em>id_map={}</em>, <em>num_iterations=1</em>, <em>raw_predictions_file='/tmp/raw_predictions'</em>, <em>model_file='/tmp/model'</em>, <em>pid_file='/tmp/vw_pid_file'</em>, <em>**vw_args</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/vw.html#VWClassifier"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.vw.VWClassifier" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="seldon.pipeline.html#seldon.pipeline.pandas_pipelines.BasePandasEstimator" title="seldon.pipeline.pandas_pipelines.BasePandasEstimator"><code class="xref py py-class docutils literal"><span class="pre">seldon.pipeline.pandas_pipelines.BasePandasEstimator</span></code></a>, <code class="xref py py-class docutils literal"><span class="pre">sklearn.base.BaseEstimator</span></code>, <code class="xref py py-class docutils literal"><span class="pre">sklearn.base.ClassifierMixin</span></code></p>
<p>Wrapper for Vowpall Wabbit classifier with pandas support</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>target</strong> (<em>str</em>) – Target column</li>
<li><strong>target_readable</strong> (<em>str</em>) – More descriptive version of target variable</li>
<li><strong>included</strong> (<em>list str, optional</em>) – columns to include</li>
<li><strong>excluded</strong> (<em>list str, optional</em>) – columns to exclude</li>
<li><strong>id_map</strong> (<em>dict (int,str), optional</em>) – map of class ids to high level names</li>
<li><strong>num_iterations</strong> (<em>int</em>) – number of iterations over data to run vw</li>
<li><strong>raw_predictions_file</strong> (<em>str</em>) – file to push raw predictions from vw to</li>
<li><strong>model_file</strong> (<em>str</em>) – model filename</li>
<li><strong>pid_file</strong> (<em>str</em>) – file to store pid of vw server so we can terminate it</li>
<li><strong>vw_args</strong> (<em>optional dict</em>) – extra args to pass to vw</li>
</ul>
</td>
</tr>
</tbody>
</table>
<dl class="method">
<dt id="seldon.vw.VWClassifier.__getstate__">
<code class="descname">__getstate__</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/vw.html#VWClassifier.__getstate__"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.vw.VWClassifier.__getstate__" title="Permalink to this definition">¶</a></dt>
<dd><p>Remove things that should not be pickled</p>
</dd></dl>
<dl class="method">
<dt id="seldon.vw.VWClassifier.__setstate__">
<code class="descname">__setstate__</code><span class="sig-paren">(</span><em>dict</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/vw.html#VWClassifier.__setstate__"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.vw.VWClassifier.__setstate__" title="Permalink to this definition">¶</a></dt>
<dd><p>Add thread based variables when creating</p>
</dd></dl>
<dl class="method">
<dt id="seldon.vw.VWClassifier.close">
<code class="descname">close</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/vw.html#VWClassifier.close"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.vw.VWClassifier.close" title="Permalink to this definition">¶</a></dt>
<dd><p>Shutdown the vw process</p>
</dd></dl>
<dl class="method">
<dt id="seldon.vw.VWClassifier.fit">
<code class="descname">fit</code><span class="sig-paren">(</span><em>X</em>, <em>y=None</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/vw.html#VWClassifier.fit"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.vw.VWClassifier.fit" title="Permalink to this definition">¶</a></dt>
<dd><p>Convert data to vw lines and then train for required iterations</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>X</strong> (<em>pandas dataframe or array-like</em>) – training samples</li>
<li><strong>y</strong> (<em>array like, required for array-like X and not used presently for pandas dataframe</em>) – class labels</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"><ul class="simple">
<li><strong>self</strong> (<em>object</em>)</li>
<li><em>Caveats</em></li>
<li><strong>1. A seldon specific fork of wabbit_wappa is needed to allow vw to run in server mode without save_resume. Save_resume seems to cause issues with the scores returned. Maybe connected to https</strong> (<em>//github.com/JohnLangford/vowpal_wabbit/issues/262</em>)</li>
</ul>
</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="seldon.vw.VWClassifier.predict_proba">
<code class="descname">predict_proba</code><span class="sig-paren">(</span><em>X</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/vw.html#VWClassifier.predict_proba"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.vw.VWClassifier.predict_proba" title="Permalink to this definition">¶</a></dt>
<dd><p>Create predictions. Start a vw process. Convert data to vw format and send.
Returns class probability estimates for the given test data.</p>
<dl class="docutils">
<dt>X <span class="classifier-delimiter">:</span> <span class="classifier">pandas dataframe or array-like</span></dt>
<dd>Test samples</dd>
</dl>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body"><ul class="simple">
<li><strong>proba</strong> (<em>array-like, shape = (n_samples, n_outputs)</em>) –
Class probability estimates.</li>
<li><em>Caveats</em></li>
<li><strong>1. A seldon specific fork of wabbit_wappa is needed to allow vw to run in server mode without save_resume. Save_resume seems to cause issues with the scores returned. Maybe connected to https</strong> (<em>//github.com/JohnLangford/vowpal_wabb#it/issues/262</em>)</li>
</ul>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
</div>
<div class="section" id="module-seldon.xgb">
<span id="seldon-xgb-module"></span><h2>seldon.xgb module<a class="headerlink" href="#module-seldon.xgb" title="Permalink to this headline">¶</a></h2>
<dl class="class">
<dt id="seldon.xgb.XGBoostClassifier">
<em class="property">class </em><code class="descclassname">seldon.xgb.</code><code class="descname">XGBoostClassifier</code><span class="sig-paren">(</span><em>target=None</em>, <em>target_readable=None</em>, <em>included=None</em>, <em>excluded=None</em>, <em>clf=None</em>, <em>id_map={}</em>, <em>vectorizer=None</em>, <em>svmlight_feature=None</em>, <em>max_depth=3</em>, <em>learning_rate=0.1</em>, <em>n_estimators=100</em>, <em>silent=True</em>, <em>objective='reg:linear'</em>, <em>nthread=-1</em>, <em>gamma=0</em>, <em>min_child_weight=1</em>, <em>max_delta_step=0</em>, <em>subsample=1</em>, <em>colsample_bytree=1</em>, <em>colsample_bylevel=1</em>, <em>reg_alpha=0</em>, <em>reg_lambda=1</em>, <em>scale_pos_weight=1</em>, <em>base_score=0.5</em>, <em>seed=0</em>, <em>missing=None</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/xgb.html#XGBoostClassifier"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.xgb.XGBoostClassifier" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="seldon.pipeline.html#seldon.pipeline.pandas_pipelines.BasePandasEstimator" title="seldon.pipeline.pandas_pipelines.BasePandasEstimator"><code class="xref py py-class docutils literal"><span class="pre">seldon.pipeline.pandas_pipelines.BasePandasEstimator</span></code></a>, <code class="xref py py-class docutils literal"><span class="pre">sklearn.base.BaseEstimator</span></code>, <code class="xref py py-class docutils literal"><span class="pre">sklearn.base.ClassifierMixin</span></code></p>
<p>Wrapper for XGBoost classifier with pandas support
XGBoost specific arguments follow <a class="reference external" href="https://github.com/dmlc/xgboost/blob/master/python-package/xgboost/sklearn.py">https://github.com/dmlc/xgboost/blob/master/python-package/xgboost/sklearn.py</a></p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>target</strong> (<em>str</em>) – Target column</li>
<li><strong>target_readable</strong> (<em>str</em>) – More descriptive version of target variable</li>
<li><strong>included</strong> (<em>list str, optional</em>) – columns to include</li>
<li><strong>excluded</strong> (<em>list str, optional</em>) – columns to exclude</li>
<li><strong>id_map</strong> (<em>dict (int,str), optional</em>) – map of class ids to high level names</li>
<li><strong>num_iterations</strong> (<em>int</em>) – number of iterations over data to run vw</li>
<li><strong>raw_predictions</strong> (<em>str</em>) – file to push raw predictions from vw to</li>
<li><strong>max_depth</strong> (<em>int</em>) – Maximum tree depth for base learners.</li>
<li><strong>learning_rate</strong> (<em>float</em>) – Boosting learning rate (xgb’s “eta”)</li>
<li><strong>n_estimators</strong> (<em>int</em>) – Number of boosted trees to fit.</li>
<li><strong>silent</strong> (<em>boolean</em>) – Whether to print messages while running boosting.</li>
<li><strong>objective</strong> (<em>string</em>) – Specify the learning task and the corresponding learning objective.</li>
<li><strong>nthread</strong> (<em>int</em>) – Number of parallel threads used to run xgboost.</li>
<li><strong>gamma</strong> (<em>float</em>) – Minimum loss reduction required to make a further partition on a leaf node of the tree.</li>
<li><strong>min_child_weight</strong> (<em>int</em>) – Minimum sum of instance weight(hessian) needed in a child.</li>
<li><strong>max_delta_step</strong> (<em>int</em>) – Maximum delta step we allow each tree’s weight estimation to be.</li>
<li><strong>subsample</strong> (<em>float</em>) – Subsample ratio of the training instance.</li>
<li><strong>colsample_bytree</strong> (<em>float</em>) – Subsample ratio of columns when constructing each tree.</li>
<li><strong>colsample_bylevel</strong> (<em>float</em>) – Subsample ratio of columns for each split, in each level.</li>
<li><strong>reg_alpha</strong> (<em>float (xgb's alpha)</em>) – L2 regularization term on weights</li>
<li><strong>reg_lambda</strong> (<em>float (xgb's lambda)</em>) – L1 regularization term on weights</li>
<li><strong>scale_pos_weight</strong> (<em>float</em>) – Balancing of positive and negative weights.</li>
<li><strong>base_score</strong> – The initial prediction score of all instances, global bias.</li>
<li><strong>seed</strong> (<em>int</em>) – Random number seed.</li>
<li><strong>missing</strong> (<em>float, optional</em>) – Value in the data which needs to be present as a missing value. If
None, defaults to np.nan.</li>
</ul>
</td>
</tr>
</tbody>
</table>
<dl class="method">
<dt id="seldon.xgb.XGBoostClassifier.fit">
<code class="descname">fit</code><span class="sig-paren">(</span><em>X</em>, <em>y=None</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/xgb.html#XGBoostClassifier.fit"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.xgb.XGBoostClassifier.fit" title="Permalink to this definition">¶</a></dt>
<dd><p>Fit a model:</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
<li><strong>X</strong> (<em>pandas dataframe or array-like</em>) – training samples. If pandas dataframe can handle dict of feature in one column or cnvert a set of columns</li>
<li><strong>y</strong> (<em>array like, required for array-like X and not used presently for pandas dataframe</em>) – class labels</li>
</ul>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first"><strong>self</strong></p>
</td>
</tr>
<tr class="field-odd field"><th class="field-name">Return type:</th><td class="field-body"><p class="first last">object</p>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="method">
<dt id="seldon.xgb.XGBoostClassifier.predict_proba">
<code class="descname">predict_proba</code><span class="sig-paren">(</span><em>X</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/xgb.html#XGBoostClassifier.predict_proba"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.xgb.XGBoostClassifier.predict_proba" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns class probability estimates for the given test data.</p>
<dl class="docutils">
<dt>X <span class="classifier-delimiter">:</span> <span class="classifier">pandas dataframe or array-like</span></dt>
<dd>Test samples</dd>
</dl>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body"><strong>proba</strong> –
Class probability estimates.</td>
</tr>
<tr class="field-even field"><th class="field-name">Return type:</th><td class="field-body">array-like, shape = (n_samples, n_outputs)</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
</div>
<div class="section" id="module-seldon.tensorflow_wrapper">
<span id="seldon-tensorflow-wrapper-module"></span><h2>seldon.tensorflow_wrapper module<a class="headerlink" href="#module-seldon.tensorflow_wrapper" title="Permalink to this headline">¶</a></h2>
<dl class="class">
<dt id="seldon.tensorflow_wrapper.TensorFlowWrapper">
<em class="property">class </em><code class="descclassname">seldon.tensorflow_wrapper.</code><code class="descname">TensorFlowWrapper</code><span class="sig-paren">(</span><em>session</em>, <em>tf_input</em>, <em>tf_output</em>, <em>tf_constants=()</em>, <em>tmp_model='/tmp'</em>, <em>target=None</em>, <em>target_readable=None</em>, <em>included=None</em>, <em>excluded=None</em>, <em>id_map={}</em><span class="sig-paren">)</span><a class="reference internal" href="modules/seldon/tensorflow_wrapper.html#TensorFlowWrapper"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#seldon.tensorflow_wrapper.TensorFlowWrapper" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="seldon.pipeline.html#seldon.pipeline.pandas_pipelines.BasePandasEstimator" title="seldon.pipeline.pandas_pipelines.BasePandasEstimator"><code class="xref py py-class docutils literal"><span class="pre">seldon.pipeline.pandas_pipelines.BasePandasEstimator</span></code></a>, <code class="xref py py-class docutils literal"><span class="pre">sklearn.base.BaseEstimator</span></code></p>
<p>Wrapper for tensorflow with pandas support</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
<li><strong>session</strong> (<em>tensorflow session</em>) – Contains the tensorflow model</li>
<li><strong>tf_input</strong> (<em>tensorflow variable</em>) – Variable used as the model input</li>
<li><strong>tf_output</strong> (<em>tensorflow variable</em>) – Variable used as the model output</li>