21
Class Imbalances
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Preface
News
Contributing
Introduction
1
Introduction
2
The Whole Game
Preparation
3
Initial Data Splitting
4
Missing Data
5
Transforming Numeric Predictors
6
Working with Categorical Predictors
7
Embeddings
8
Interactions and Nonlinear Features
Optimization
9
Overfitting
10
Measuring Performance with Resampling
11
Grid Search
12
Iterative Search
13
Feature Selection
14
Comparing Models
Classification
15
Characterizing Classification Models
16
Generalized Linear and Additive Classifiers
17
Complex Nonlinear Boundaries
18
Neural Network Classifiers
19
Classification using Trees and Rules
20
Classification Ensembles
21
Class Imbalances
22
Classification Case Study
23
Classification Summary
Regression
Characterization
Finalization
21
Class Imbalances
20
Classification Ensembles
22
Classification Case Study