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Date
Day
Topic
Download
Comments
1
3/9/2013
Tuesday
Course Overview, What is Data Mining and its Origin, Typical Data Mining Tasks, Data Mining Applications/Examples


2
5/9/2013
Thursday
Data Mining vs. OLAP and Statistics, Data Preparation, Normalization, Outlier Detection


3
10/9/2013
Tuesday
Unit # 2 (Cont'd), Feature Reduction/Ranking using Mean-Variance Method, Sampling Size, Introduction to Classification/Decision Trees, Model Interpretation, Measures of Node Impurity, Computation of GINI Index,


4
17/9/2013
Tuesday
Computation of Entropy and Misclassification Error, Induction of Classification Trees, Handling of Continuous Data, ChiMerge Discretization


5
19/9/2013
Thursday
Handling of Multi-state Data, Discretization using Value Reduction


6
24/9/2013
Tuesday
Model Evaluation, Accuracy, Weighted Accuracy, Recall and Precision, Weka Demo, Receiver Operating Characteristics (ROC Curve), Lift and Gain Charts,


7
26/9/2013
Thursday
KNIME Demo, Lab Session: Weka and KNIME


8
1/10/2013
Tuesday
Bayes Theorem, Naive Bayes Classifier


9
3/10/2013
Thursday
Entropy-based Feature Selection, Revision before Midterm 1


10
22/10/2013
Tuesday
Artificial Neural Networks, Motivation, History, Multi-layer Feedforward Network, Backpropagation Algorithm


11
24/10/2013
Thursday
Lazy Learner vs. Eager Learner, k-Nearest Neighbor: Pros and Cons


12
29/10/2013
Tuesday
Model Evaluation (Holdout, k-Cross Validation), Sampling with Replacement (Bootsrapping), Ensemble Methods (Bagging and Boosting), Stacking


13
31/10/2013
Thursday
Presentations: Homework 1


14
5/11/2013
Tuesday
Presentations: Homework 1


15-16
17/11/2013
Sunday
Clustering: Basic Concepts and Popular Types, Applications, K-Means: Concepts, Working, Limitations, Schemes to Handle Initial Centroid Problems in K-Means,
Hierarchical Clustering: Simple/Complete/Average Linkages, Validity of Clusters: External and Internal Metrics


17
19/11/2013
Tuesday
Distance Computation for Mixed Type Variables: Interval-Scaled, Symmetric and Asymmetric Binary, Categorical and Ordinal, Fuzzy c-Means


18
21/11/2013
Thursday
Project 1 Presentation


19
3/12/2013
Tuesday
Kohonen Maps, Clustering using Adaptive Resonance Theory (ART), KNIME Demo (Clustering)


20
5/12/2013
Thursday
Association Rule Mining, Apriori Algorithm, Frequent Itemsets and Rules Generation, Support, Confidence, Interest and Lift


21
10/12/2013
Tuesday
KNIME Demo, Handling of Continuous and Categorical Data, min-Apriori, Multi-level Association Rules, Discussion on Case Studies (from Implementing Analytics, Chapter 3)


22
12/12/2013
Thursday
Text Mining, KNIME Demo


23-24
15/12/2013
Sunday
Covariance Matrix, Eigenvalues and Eigenvectors, Principal Component Analysis, R and KNIME implementation of PCA, Guest Lecture by Mr. Nauman Sheikh


25
19/12/2013
Thursday
Unit # 18 (Cont'd), Introduction to R Programming


26
26/12/2013
Thursday
Overview of Big Data


27
31/12/2013

Project 2 Presentations


28
2/1/2014

Project 2 Presentations