Course Materials
Textbook: R을 이용한 데이터마이닝 · Reference: Datamining with R
R Code & Examples
- TXTCode 1
- TXTCode 2
- TXTCode 3
- TXTChapter 2 Essentials
- TXTKNN Imputation
- TXTMy Imputation Code
- TXTAlgae Data Imputation and Model Fitting
- TXTCategorical Variables Encoding
- TXTPerformance Check Using CV
- TXTPerformance Comparison: Classification Methods Using Iris Data
- PDFClassification F-score and ROC Thanks to J. Kim
- TXTPerformance Comparison: Credit Card Approval Data
- TXTFind the Optimal Tree
Classification & Clustering
- HTMLClustering
- HTMLClustering Example
- PDFClassification
- PDFLogistic Regression with R (Data) Thanks to Prof. Jerry Brunner, University of Toronto
- TXTLogistic Regression with Group Count Data
- HTMLLDA
- PDFSVM Guide
- PDFLift Chart
- TXTSVM Classification Example
- TXTSVM Regression R Code
- LINKSVM 설명 1
- LINKSVM 설명 2
Ensemble Methods & Deep Learning
- LINKRandom Forest Tutorial
- HTMLranger Tutorial with Housing Data
- PDFGradient Boosting 설명
- LINKGradient Boosting Tutorial
- RXGBoost Example
- RWine 데이터 분석
- RAdult 데이터 분석
- PDFPartial Dependence Plot (pdp)
- TXTPartial Dependence Plot Example (pdp)
- PDF예측모형에서 범주형 변수 처리
- TXTvtreat Example
- PDFDeep Learning 1 Thanks to Lee, H.
- PDFDeep Learning 2 Thanks to Lee, H.
- LINKKeras for R