Caret Package in R

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Section 1:Overview

  1. What is caret
  2. How to Get Queries Resolved
  3. Problem Statement
  4. Download Resources

Section 2: Data Processing

  1. Sampling Approaches
  2. Missing Value Treatment
  3. One Hot Encoding

Section 3: Data Transformation

  1. Box Cox Transformation Concept
  2. Applying Box Cox and PCA
  3. Course Review

Section 4: EDA

  1. Feature Plots
  2. Statistical Analysis

Section 5: Feature Selection

  1. Recursive Feature Elimination (RFE) Algorithm
  2. Recursive Feature Elimination (RFE Demo)
  3. Course Review

Section 6: Genetic Algorithms

  1. Genetic Algorithms
  2. Dependency Parsing
  3. Genetic Algorithms part 2 - Feature Selection
  4. Genetic Algorithms Demo

Section 7: Annealing Algorithm

  1. Simulated Annealing Concept
  2. Simulated Annealing Demo
  3. Course Review
  4. Exploring the ML Models (BIG LIST)

Section 8: ML Algorithms

  1. Building ML with train function
  2. Course Review

Section 9: ML Model Improvement

  1. Automatic Hyperparameter Tuning
  2. Customize Hyperparameter Search
  3. Comparing Adaboost xgboost random forest and svm
  4. Tuning Non Default Parameters with Caret
  5. Caret Ensemble
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