update fit a line

01.fit_a_line/README.cn.md

@@ -143,17 +143,25 @@ feature_names = [
     'CRIM', 'ZN', 'INDUS', 'CHAS', 'NOX', 'RM', 'AGE', 'DIS', 'RAD', 'TAX',
     'PTRATIO', 'B', 'LSTAT', 'convert'
 ]
+
 feature_num = len(feature_names)
+
 data = numpy.fromfile(filename, sep=' ') # 从文件中读取原始数据
+
 data = data.reshape(data.shape[0] // feature_num, feature_num)
+
 maximums, minimums, avgs = data.max(axis=0), data.min(axis=0), data.sum(axis=0)/data.shape[0]
 
 for i in six.moves.range(feature_num-1): # six.moves可以兼容python2和python3
+
     data[:, i] = (data[:, i] - avgs[i]) / (maximums[i] - minimums[i])
 
 ratio = 0.8 # 训练集和验证集的划分比例
+
 offset = int(data.shape[0]*ratio)
+
 train_data = data[:offset]
+
 test_data = data[offset:]
 
 train_reader = paddle.batch(

01.fit_a_line/index.cn.html

@@ -185,17 +185,25 @@ feature_names = [
     'CRIM', 'ZN', 'INDUS', 'CHAS', 'NOX', 'RM', 'AGE', 'DIS', 'RAD', 'TAX',
     'PTRATIO', 'B', 'LSTAT', 'convert'
 ]
+
 feature_num = len(feature_names)
+
 data = numpy.fromfile(filename, sep=' ') # 从文件中读取原始数据
+
 data = data.reshape(data.shape[0] // feature_num, feature_num)
+
 maximums, minimums, avgs = data.max(axis=0), data.min(axis=0), data.sum(axis=0)/data.shape[0]
 
 for i in six.moves.range(feature_num-1): # six.moves可以兼容python2和python3
+
     data[:, i] = (data[:, i] - avgs[i]) / (maximums[i] - minimums[i])
 
 ratio = 0.8 # 训练集和验证集的划分比例
+
 offset = int(data.shape[0]*ratio)
+
 train_data = data[:offset]
+
 test_data = data[offset:]
 
 train_reader = paddle.batch(