Reference: https://zhuanlan.zhihu.com/p/36287950
Todo List
- [X] - 01 - Overview
P1-15 Machine learning background and flow
P16-42 Machine learning flow
[ ] - 02 - Business Understanding
[X] - 03 - Data Understanding p56 - 62
To learn about data analysis, it is right that each of us try many things that do not work – that we tackle more problems than we make expert analyses of. We often learn less from an expertly done analysis than from one where, by not trying something, we missed an opportunity to learn more
[ ] - 04 - Data Preparation -p63
Prepare data is time consuming
several methods to deal with missing data and outliers
normalize Data
Data binning 分级
Reduce Data, Clean Data
Feature Engineering: 从raw data 提取出 feature
Feature Selection: Filter/Wrapper/Embedded method
Traditional approaches 传统方法
Forward selection
一开始模型里面没有variable， 然后往里面加入variable，直到accuracy 没有任何的增长
Backward elimination
和前一种相反，一开始有所有的variable, 然后去除，直到accuracy 有明显的下降
Stepwise regression
这种是用在选k-best feature， 一开始有k个，然后加入更好的，并且去除最差的，直到经历过所有的feature
P100