wehub-resource-sync
53 lines
1.3 KiB
Python
Executable File
53 lines
1.3 KiB
Python
Executable File
import numpy as np
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from prml.linear.classifier import Classifier
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class Perceptron(Classifier):
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"""
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Perceptron model
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"""
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def fit(self, X, t, max_epoch=100):
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"""
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fit perceptron model on given input pair
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Parameters
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----------
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X : (N, D) np.ndarray
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training independent variable
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t : (N,)
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training dependent variable
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binary -1 or 1
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max_epoch : int, optional
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maximum number of epoch (the default is 100)
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"""
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self.w = np.zeros(np.size(X, 1))
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for _ in range(max_epoch):
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N = len(t)
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index = np.random.permutation(N)
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X = X[index]
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t = t[index]
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for x, label in zip(X, t):
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self.w += x * label
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if (X @ self.w * t > 0).all():
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break
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else:
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continue
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break
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def classify(self, X):
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"""
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classify input data
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Parameters
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----------
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X : (N, D) np.ndarray
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independent variable to be classified
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Returns
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-------
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(N,) np.ndarray
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binary class (-1 or 1) for each input
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"""
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return np.sign(X @ self.w).astype(np.int)
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