Generalized Linear Modeling with H2O's R Package
Generalized Linear Modeling with H2O's R Package
About the Book
About the Author
Table of Contents
- What is H2o
-
What is GLM?
- GLM on H2O
- Summary of Features
-
Installation
- Support
-
Generalized Linear Modeling
- Model Fitting
- Model Validation
- Regularization
- Lasso
- Elastic Net Penalty
-
GLM Models
- Linear Regression (Gaussian Family)
- Logistic Regression (Binomial Family)
- Poisson Models
- Gamma Models
-
GLM on H2o
- Input Parameters
- Coefficient Constraints
- H2O GLM Model Output
- Coefficients and Normalized Coefficients
- Validation
- Generating Predictions
- Categorical Variables
- Largest Categorical Trick
- Cross Validation
- Selecting Regularization Parameters
- Grid Search over Alpha
- Lambda Search
- Grid Search over Lambdas
- Strong Rules
- Performance Characteristics
-
Use Case: Classification with Airline Data
- Airline Dataset Overview
- Loading Data
- Performing a Trial Run
- Extracting and Handling the Results
- Web Interface
- Variable Importances
- Java Model
- Appendix: Parameters
- References
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