/multivariate-data-analysis

Multivariate data analysis @Korea University (Undergraduate)

Primary LanguageR

multivariate-data-analysis

Multivariate data analysis @Korea University (Undergraduate)

Week 1: Introduction to R (Part 1)

  • R Overview
  • Handling different data types
  • Text processing

Week 2: Introduction to R (Part 2)

  • Conditions and loops in R
  • R functions
  • R graphics
  • Documentation

Week 3: Association Rule Mining

  • A Priori algorithm
  • ARM applications
  • R exercise

Week 4: Clustering

  • Goals and issues in clustering
  • K-Means clustering
  • Hierarchical clustering
  • R exercise

Week 5: Multiple Linear Regression

  • Multiple linear regression: ordinary least squares (OLS)
  • Evaluating the performance of regression algorithms
  • Supervised variable selection
  • MLR application: Forecasting box office with SNS data
  • R Exercise

Week 6: Logistic Regression

  • Logistic regression
  • Statistical properties of regression coefficients
  • R exercise

Week 7: k-Nearest Neighbor Learning

  • k-NN classification
  • k-NN regression
  • Evaluating the performance of classification algorithms
  • R exercise

Week 8: Naive Bayesian Classifier & Linear Discriminant Analysis

  • Baye's Rule and Naive Bayesian classifier
  • Linear discriminant analysis
  • R exercise

Week 9-10: Deecision Tree

  • Classification Tree
  • Regression Tree
  • R exercise

Week 11-12: Artificial Neural Network

  • Neural network structure
  • Activation function
  • Learning neural network
  • Avoid overfitting
  • R exercise

Week 13-14: Ensemble Learning

  • Bootstrapping (Bagging): ANN and DT
  • Random Forests
  • R exercise