更新 15项目案例

src/python/15.BigData_MapReduce/pegasos.py

@@ -1,12 +1,14 @@
+#!/usr/bin/python
+# coding:utf8
 '''
 Created on 2017-04-07
 Sequential Pegasos 
 the input T is k*T in Batch Pegasos
 @author: Peter/ApacheCN-xy
 '''
-
 from numpy import *
 
+
 def loadDataSet(fileName):
     dataMat = []; labelMat = []
     fr = open(fileName)
@@ -17,6 +19,7 @@ def loadDataSet(fileName):
         labelMat.append(float(lineArr[2]))
     return dataMat,labelMat
 
+
 def seqPegasos(dataSet, labels, lam, T):
     m,n = shape(dataSet); w = zeros(n)
     for t in range(1, T+1):
@@ -29,10 +32,12 @@ def seqPegasos(dataSet, labels, lam, T):
             w = (1.0 - 1/t)*w
         print w
     return w
-        
+
+
 def predict(w, x):
     return w*x.T
 
+
 def batchPegasos(dataSet, labels, lam, T, k):
     m,n = shape(dataSet); w = zeros(n); 
     dataIndex = range(m)
@@ -48,6 +53,8 @@ def batchPegasos(dataSet, labels, lam, T, k):
         w = (1.0 - 1/t)*w + (eta/k)*wDelta       # 在每个 T上应用更改
     return w
 
+
+
 datArr,labelList = loadDataSet('testSet.txt')
 datMat = mat(datArr)
 #finalWs = seqPegasos(datMat, labelList, 2, 5000)
@@ -74,4 +81,4 @@ ax.plot(x,y)
 ax.plot(x,y2,'g-.')
 ax.axis([-6,8,-4,5])
 ax.legend(('50 Iterations', '2 Iterations') )
-plt.show()
+plt.show()