July 2017
Intermediate to advanced
254 pages
6h 29m
English
Content preview from Mastering Machine Learning with scikit-learn - Second Edition
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Scaling features
Many learning algorithms work better when features take similar ranges of values. In the previous section, we used two features: a binary-valued feature representing the person's sex and a continuous-valued feature representing the person's height in centimeters. Consider a dataset in which we have a man who is 170 cm tall and a woman who is 160 cm tall.
Which instance is closer to a man who is 164 cm tall? For our weight prediction problem, we probably believe that the query is closer to the male instance; a 6 cm difference in height is less important to predicting weight than the difference between sexes. If we represent the height in millimeters, the query instance is closer to the 1600 mm tall female. If we represent ...
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