wehub-resource-sync
33 lines
1.0 KiB
Python
33 lines
1.0 KiB
Python
from __future__ import print_function
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from sklearn import datasets
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import numpy as np
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import matplotlib.pyplot as plt
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# Import helper functions
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from mlfromscratch.utils import make_diagonal, normalize, train_test_split, accuracy_score
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from mlfromscratch.deep_learning.activation_functions import Sigmoid
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from mlfromscratch.utils import Plot
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from mlfromscratch.supervised_learning import LogisticRegression
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def main():
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# Load dataset
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data = datasets.load_iris()
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X = normalize(data.data[data.target != 0])
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y = data.target[data.target != 0]
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y[y == 1] = 0
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y[y == 2] = 1
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X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, seed=1)
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clf = LogisticRegression(gradient_descent=True)
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clf.fit(X_train, y_train)
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y_pred = clf.predict(X_test)
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accuracy = accuracy_score(y_test, y_pred)
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print ("Accuracy:", accuracy)
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# Reduce dimension to two using PCA and plot the results
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Plot().plot_in_2d(X_test, y_pred, title="Logistic Regression", accuracy=accuracy)
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if __name__ == "__main__":
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main() |