56 lines
1.3 KiB
Python
56 lines
1.3 KiB
Python
# -*- coding: utf-8 -*-
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"""
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Created on Wed Sep 24 10:18:50 2014
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@author: clemens
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"""
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from sklearn.datasets import make_blobs
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from sklearn.lda import LDA
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import matplotlib.pyplot as plt
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import numpy as np
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def plot_data(X, y):
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for label, marker, color in zip(np.unique(y), ("x", "o"), ("blue", "red")):
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plt.scatter(x=X[y == label, 0], y=X[y == label, 1], marker=marker, color=color)
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def plot_boundary(clf):
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nx, ny = 200, 100
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x_min, x_max = plt.xlim()
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y_min, y_max = plt.ylim()
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xx, yy = np.meshgrid(np.linspace(x_min, x_max, nx),
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np.linspace(y_min, y_max, ny))
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Z = clf.predict_proba(np.c_[xx.ravel(), yy.ravel()])
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Z = Z[:, 1].reshape(xx.shape)
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plt.contour(xx, yy, Z, [0.5], linewidths=2., colors='k')
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# Generate data
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X, y = make_blobs(n_samples=100, n_features=2, centers=[[-2, 5], [0, 3.5]])
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clf1 = LDA(solver="svd", store_covariance=True)
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clf2 = LDA(solver="lsqr", alpha=None)
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clf3 = LDA(solver="eigen", alpha=None)
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clf1.fit(X, y)
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clf2.fit(X, y)
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clf3.fit(X, y)
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plt.figure(1)
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plt.subplot(1, 3, 1)
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plot_data(X, y)
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plot_boundary(clf1)
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plt.title("svd")
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plt.subplot(1, 3, 2)
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plot_data(X, y)
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plot_boundary(clf2)
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plt.title("lsqr")
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plt.subplot(1, 3, 3)
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plot_data(X, y)
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plot_boundary(clf3)
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plt.title("eigen")
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plt.show()
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