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Gaussian naive Bayes algorithm #128

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Gaussian naive Bayes algorithm #128

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d25bc31
adaboost classifier to predict brest cancer
balde9745 Nov 19, 2020
dcd6aba
gaussian naive bayes to classify flours iris dataset
balde9745 Nov 19, 2020
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gaussian naive bayes to classify flours iris dataset
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@balde9745
balde9745 committed Nov 19, 2020
commit dcd6aba9e9dc5db5aef9bef6aeffe3e103978cd8
32 changes: 32 additions & 0 deletions classification/gaussian_n_bayes.py
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# importing libraries
from sklearn.naive_bayes import GaussianNB
from sklearn.model_selection import train_test_split
from sklearn.datasets import load_iris
from sklearn.metrics import accuracy_score, classification_report
import pandas as pd


"""To implement Gaussian naves bayes for flowers clssification"""


def main():

iris = load_iris()
print(iris.keys())
iris_df = pd.DataFrame(iris.data, columns=iris.feature_names)
iris_df['target'] = iris.target
print(iris_df.head())
X, y = iris_df.drop('target', 1), iris_df.target
print(X.shape, y.shape)
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42)
model = GaussianNB()
model.fit(X_train, y_train)
y_pred = model.predict(X_test)
print(y_pred[:10])
accuracy = accuracy_score(y_test, y_pred)
print("The accuracy of Gaussian naves is {}".format(accuracy))
# classification report
print(classification_report(y_test, y_pred))


main()