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5 Standard Machine Learning Datasets 25
5.1 Practice On Small Well-Understood Dat a set s .................... 25
5.2 Package: datasets ................................... 26
5.3 Package: mlbench ................................... 27
5.4 Package: AppliedPredictiveModeling ........................ 34
5.5 Summary ....................................... 35
6 Load Your Machine Learning Datasets 36
6.1 Access To Your Data ................................. 36
6.2 Load Data Fro m CSV File .............................. 37
6.3 Load Data Fro m CSV URL ............................. 37
6.4 Summary ....................................... 38
7 Understand Your Da t a Using Descriptive Statistics 39
7.1 You Must Under st an d Your Data .......................... 39
7.2 Peek At Your Data .................................. 40
7.3 Dimensions of Your Data ............................... 41
7.4 Data Typ es ...................................... 41
7.5 Class Distribution ................................... 42
7.6 Data Summary .................................... 42
7.7 Standard Deviations ................................. 43
7.8 Skewness ........................................ 44
7.9 Correlations ...................................... 44
7.10 Tips To Remember .................................. 45
7.11 Summary ....................................... 45
8 Understand Your Data Using Data Visualization 47
8.1 Understand You r Data To Get The Best Results .................. 47
8.2 Visualization Packages ................................ 48
8.3 Univariate Visual i zat i o n ............................... 48
8.4 Multivariate Visu a l i zat i o n .............................. 52
8.5 Tips For Data Vi s u al i za t i on ............................. 57
8.6 Summary ....................................... 58
9 Prepare Your Dat a For Machine Learning With Pre-Processing 59
9.1 Need For Data Pre -Pr ocessing ............................ 59
9.2 Data Pre-Processing in R ............................... 60
9.3 Scale Data ....................................... 61
9.4 Center Data ...................................... 62
9.5 Standardize Data ................................... 63
9.6 Normalize Data .................................... 63
9.7 Box-Cox Transform .................................. 64
9.8 Yeo-Johnson Transform ................................ 65
9.9 Principal Component Analysis Transform ...................... 66
9.10 In d ependent Component Analysis Transform .................... 67
9.11 Tips For Data Transforms .............................. 69
9.12 Summary ....................................... 69
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