wehub-resource-sync
31 lines
969 B
Python
31 lines
969 B
Python
from __future__ import division, print_function
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import numpy as np
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from sklearn import datasets
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# Import helper functions
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from mlfromscratch.utils import train_test_split, normalize, accuracy_score, Plot
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from mlfromscratch.utils.kernels import *
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from mlfromscratch.supervised_learning import SupportVectorMachine
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def main():
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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] = -1
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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)
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clf = SupportVectorMachine(kernel=polynomial_kernel, power=4, coef=1)
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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="Support Vector Machine", accuracy=accuracy)
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if __name__ == "__main__":
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main() |