Syllabus

Introduction (chap 1)

• History
• Definitions
• Data Mining Tasks
• Data Mining standards

Data (chap 2)

• Data Attributes
• Data Preprocessing
• Similarity Measures

Exploring Data (chap 3)

• Summary Statistics
• Visualization
• OLAP and Multidimensional Data Analysis

Overview of Predictive Learning & Function Approximation (tentative)

• Meet @ SPMS-LT5 (new School next to Canteen B, south spine)
• Based on Friedman's 1994 paper of the same name

Classification 1 (chap 4)

• Decision Trees
• Model Overfitting
• Bias/Variance
• Comparing Classifiers

Classification 2 (chap 5)

• Rule-Based Classifier
• Nearest Neighbour Classifier
• Bayesisan Classifiers
• Artificial Neural Network (ANN)
• Support Vector Machine (SVM)
• Ensemble Methods
• Class Imbalance Problem

Lab 1 of 2 (self-paced)

• 2 registered students to share one machine
  • Sorry, due to limited machines, we can only accomodate registered students
• Meet @ CR7 (optional for those who do not know the way)
• Walk to N4-b3c-14 (CAIS) @ 6:45 pm
• Getting familar with SAS Enterprise Miner
  • Download (and optionally print & bind) from SAS the following 150+ page document:
  • Lab1 (local copy)
    
  •  Lab1 (from SAS)
    
  • Also download the Lab1 dataset during the lab
  • Lab1 dataset (local copy)
    
  • Lab1 dataset (from SAS)
    
  • We will be following the tutorial in this guide.

No Lecture

Cluster Analysis 1 (chap 8)

• K-Means
• Agglomerative Hierarchical Clustering
• DBSCAN
• Cluster Evaluation

Cluster Analysis 2 (chap 9)

• Prototype-Based Clustering
• Density-Based Clustering
• Graph-Based Clustering
• Scalable Clustering Algorithms

Anomaly Detection (chap 10)

• Statistical Approaches
• Proximity-Based Outlier Detection
• Density-Based Outlier Detection
• Clustering-Based Techniques

Association Analysis 1 (chap 6)

• Frequent Itemset Generation
• Rule Generation
• Compact Representation
• Evaluation

Association Analysis 2 (chap 7)

• Handling Categorical, Continous attributes
• Handling concept hierarchy
• Sequential patterns
• subgraph patterns
• infrequent patterns

Lab 2 of 2

• Cluster Analysis
• Association Rules
• Download 28-page Lab 2 manual
• Dataset will be loaded from SAS server during lab