wehub-resource-sync
36 lines
929 B
Python
36 lines
929 B
Python
from __future__ import print_function
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from sklearn import datasets
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import matplotlib.pyplot as plt
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import numpy as np
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from mlfromscratch.supervised_learning import LDA
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from mlfromscratch.utils import calculate_covariance_matrix, accuracy_score
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from mlfromscratch.utils import normalize, standardize, train_test_split, Plot
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from mlfromscratch.unsupervised_learning import PCA
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def main():
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# Load the dataset
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data = datasets.load_iris()
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X = data.data
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y = data.target
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# Three -> two classes
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X = X[y != 2]
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y = y[y != 2]
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X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33)
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# Fit and predict using LDA
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lda = LDA()
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lda.fit(X_train, y_train)
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y_pred = lda.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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Plot().plot_in_2d(X_test, y_pred, title="LDA", accuracy=accuracy)
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if __name__ == "__main__":
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main()
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