Python readIn示例

示例#1

文件： hw7.py 项目： BadgerWIVV/edX-Learning-From-Data-Solutions

def problem1():
  name = ['c://users//mark//in.dta', 'c://users//mark//out.dta']
  in_data = dataSet(readIn(name[0]))
  out_data = dataSet(readIn(name[1]))
  X, Y = in_data
  print 'Problem 1, 2'
  for k in (3, 4, 5, 6, 7):
    X_t, Y_t = X[:25, :k+1], Y[:25]
    X_v, Y_v = X[25:, :k+1], Y[25:]
    w = regression((X_t, Y_t))
    print k, classificationError((X_v, Y_v), w), classificationError((out_data[0][:, :k+1], out_data[1]) , w)
  print 'Problem 3, 4'
  for k in (3, 4, 5, 6, 7):
    X_t, Y_t = X[:25, :k+1], Y[:25]
    X_v, Y_v = X[25:, :k+1], Y[25:]
    w = regression((X_v, Y_v))
    print k, classificationError((X_t, Y_t), w), classificationError((out_data[0][:, :k+1], out_data[1]) , w)

示例#2

文件： hw7.py 项目： zcli/edX-Learning-From-Data-Solutions

def problem1():
    name = ['c://users//mark//in.dta', 'c://users//mark//out.dta']
    in_data = dataSet(readIn(name[0]))
    out_data = dataSet(readIn(name[1]))
    X, Y = in_data
    print 'Problem 1, 2'
    for k in (3, 4, 5, 6, 7):
        X_t, Y_t = X[:25, :k + 1], Y[:25]
        X_v, Y_v = X[25:, :k + 1], Y[25:]
        w = regression((X_t, Y_t))
        print k, classificationError((X_v, Y_v), w), classificationError(
            (out_data[0][:, :k + 1], out_data[1]), w)
    print 'Problem 3, 4'
    for k in (3, 4, 5, 6, 7):
        X_t, Y_t = X[:25, :k + 1], Y[:25]
        X_v, Y_v = X[25:, :k + 1], Y[25:]
        w = regression((X_v, Y_v))
        print k, classificationError((X_t, Y_t), w), classificationError(
            (out_data[0][:, :k + 1], out_data[1]), w)

示例#3

文件： hw8.py 项目： zcli/edX-Learning-From-Data-Solutions

def getData():
    return readIn('features.train'), readIn('features.test')

示例#4

文件： hw8.py 项目： BadgerWIVV/edX-Learning-From-Data-Solutions

def getData():
  return readIn('features.train'), readIn('features.test')