均值归一化处理(Mean normalization)

1.   Suppose m=4 students have taken some class,and the class had a midterm exam and a final exam. You have collected a datasetof their scores on the two exams, which is as follows:

midterm exam

(midterm exam)2

final exam

89

7921

96

72

5184

74

94

8836

87

69

4761

78

You'd like to use polynomial regressionto predict a student's final exam score from their midterm exam score.Concretely, suppose you want to fit a model of the form , where is the midterm score and  is (midterm score)². Further, youplan to use bothfeature scaling (dividing by the "max-min", or range, of afeature) and mean normalization.

What is thenormalized feature ? (Hint: midterm = 89, final = 96 is training example 1.)Please round off your answer to two decimal places and enter in the text boxbelow.

这是cousera上ML的一道测试题，字幕翻译Mean normalization是均值归一化处理，没找到对应的中文定义。

此处的解释是，S1既可以是训练集合取值的范围：最大值和最小值之差，也可以使用标准方差。此题答案是使用训练集合取值范围计算的。

关于归一化处理的两种方法：min-max标准化和Z-score标准化方法参见：

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