解锁数据的秘密 - 使用 R 进行无监督学习
- 1. Introduction
- 1. Introduction
- 2. Instructor Welcome
- 5. Getting Data Sets
- 2. Unsupervised Learning Clustering
- 1. Introduction to Clustering
- 2. Example of using College Scorecard Data - from Industry
- 3. Getting and Loading the College Scorecard Data
- 4. Scaling The Data - Required for Clustering Analyses
- 5. Using Hierarchical Clustering in R
- 6. Running a kMeans Clustering Analysis in R
- 7. Cluster Validity
- 3. Unsupervised Learning Dimensionality Reduction
- 1. Introduction to Dimensionality Reduction
- 2. Feature Removal of Highly Correlated Features
- 3. PCA in R - Part 1
- 4. PCA in R - Part 2
- 4. Unsupervised Learning Association Rule Mining (aka Market Basket Analysis)
- 1. Introduction to Frequent Itemset Mining and Association Rule Mining - Part 1
- 2. Introduction to Frequent Itemset Mining and Association Rule Mining - Part 2
- 3. Measuring Results of Association Rules
- 4. Cleaning and Preparing Data for Frequent Itemset Mining and Association Rules
- 5. Frequent Itemsets
- 6. Association Rules
- 7. Sorting Itemsets and Rules