感知机模型python代码

感知机模型的Python代码如下：

import numpy as np

class Perceptron:
    def __init__(self, lr=0.1, n_iter=100):
        self.lr = lr
        self.n_iter = n_iter
        self.weights = None
        self.bias = None

    def fit(self, X, y):
        n_samples, n_features = X.shape
        self.weights = np.zeros(n_features)
        self.bias = 0

        for _ in range(self.n_iter):
            for i in range(n_samples):
                x = X[i]
                y_true = y[i]
                y_pred = self.predict(x)

                if y_true != y_pred:
                    self.weights += self.lr * y_true * x
                    self.bias += self.lr * y_true

    def predict(self, X):
        linear_output = np.dot(X, self.weights) + self.bias
        return np.where(linear_output >= 0, 1, -1)

其中，`fit()` 函数用于训练感知机模型，`predict()` 函数用于进行预测。在训练过程中，使用随机梯度下降算法来更新权重和偏置。