增加感知器实现类

Author: csuldw

Perceptron/Perceptron.py

@@ -0,0 +1,50 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Mon Jan 29 09:20:04 2018
+
+@author: liudiwei
+"""
+
+class Perceptron(object):
+    def __init__(self, input_num, activation_func):
+        """init parameter
+        activation_func: this is a function of activation
+        input_num: number of sample
+        """
+        self.activation_func = activation_func
+        self.weights = [0.0 for _ in range(input_num)]
+        self.bias = 0.0           
+    
+    def train(self, input_vecs, labels, iteration, rate):
+        """training model
+        input_vec: input vetcor, a 2-D list
+        labels: class label list
+        iteration: 
+        rate: learning rate
+        """
+        for i in range(iteration):
+            self._one_iteration(input_vecs, labels, rate)
+            
+    def _one_iteration(self, input_vecs, labels, rate):
+        """training model on input_vecs dataset"""
+        samples = zip(input_vecs, labels)
+        for (input_vec, class_label) in samples:
+            output_val = self.predict(input_vec)
+            self._update_weights(input_vec, output_val, class_label, rate)
+
+    def _update_weights(self, input_vec, output_val, class_label, rate):
+        """update weights for each iteration"""
+        delta = class_label - output_val
+        self.weights = map(lambda (x, w): w + rate * delta * x, 
+                           zip(input_vec, self.weights))
+        self.bias += rate * delta
+    
+    def __to_string__(self):
+        return 'weights\t: %s\nbias\t: %f\n' % (self.weights, self.bias)
+        
+    def predict(self, input_vec):
+        """input input_vec and return a prediction value"""
+        return self.activation_func(
+            reduce(lambda a, b: a + b,
+                    map(lambda (x, w): x * w, zip(input_vec, self.weights)),
+                    0.0) + self.bias)