Caret Package in R
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Section 1:Overview
- What is caret
- How to Get Queries Resolved
- Problem Statement
- Download Resources
Section 2: Data Processing
- Sampling Approaches
- Missing Value Treatment
- One Hot Encoding
- Box Cox Transformation Concept
- Applying Box Cox and PCA
- Course Review
Section 4: EDA
- Feature Plots
- Statistical Analysis
Section 5: Feature Selection
- Recursive Feature Elimination (RFE) Algorithm
- Recursive Feature Elimination (RFE Demo)
- Course Review
Section 6: Genetic Algorithms
- Genetic Algorithms
- Dependency Parsing
- Genetic Algorithms part 2 - Feature Selection
- Genetic Algorithms Demo
Section 7: Annealing Algorithm
- Simulated Annealing Concept
- Simulated Annealing Demo
- Course Review
- Exploring the ML Models (BIG LIST)
Section 8: ML Algorithms
- Building ML with train function
- Course Review
Section 9: ML Model Improvement
- Automatic Hyperparameter Tuning
- Customize Hyperparameter Search
- Comparing Adaboost xgboost random forest and svm
- Tuning Non Default Parameters with Caret
- Caret Ensemble