Machine Learning with R and H2O

May 2020: Seventh Edition

Section	Title	Page
1	Introduction	5
2	What is H2O?	6
3	Installation	7
3.1	Installing R	8
3.2	Installing H2O from R	8
3.3	Example Code	9
3.4	Citation	9
4	H2O Initialization	9
4.1	Launching from R	9
4.2	Launching from the Command Line	11
4.3	Launching on Hadoop	11
4.4	Checking Cluster Status	12
5	Data Preparation in R	12
5.1	Notes	13
6	Models	14
6.1	Supervised Learning	14
6.2	Unsupervised Learning	15
6.3	Miscellaneous	15
6.4	Modeling Constructs	15
7	Demo: GLM	15
8	Data Manipulation in R	18
8.1	Importing Files	18
8.2	Uploading Files	19
8.3	Finding Factors	19
8.4	Converting to Factors	19
8.5	Converting Data Frames	20
8.6	Transferring Data Frames	20
8.7	Renaming Data Frames	21
8.8	Viewing Column Names	21
8.9	Getting Minimum and Maximum Values	22
8.10	Getting Quantiles	22
8.11	Summarizing Data	23
8.12	Summarizing Data in a Table	24
8.13	Generating Random Numbers	25
8.14	Splitting Frames	26
8.15	Getting Frames	27
8.16	Getting Models	27
8.17	Listing H2O Objects	27
8.18	Removing H2O Objects	28
8.19	Adding Functions	28
9	Running Models	29
9.1	Gradient Boosting Machine (GBM)	29
9.2	Generalized Linear Models (GLM)	31
9.3	K-means	33
9.4	Principal Components Analysis (PCA)	34
9.5	Predictions	34
10	Appendix: Commands	35
10.1	Dataset Operations	35
10.2	General Data Operations	36
10.3	Methods from Group Generics	37
10.4	Other Aggregations	40
10.5	Data Munging	40
10.6	Data Modeling	41
10.7	H2O Cluster Operations	43
11	Acknowledgments	45
12	References	45
13	Authors	46

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Contents