Lectures

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 * **S.#** || **Date** || **Day** || **Topics** || **Download** || ** Assignments ** || **Comments** ||
 * 1 || 03/02/10 || Wednesday || Course Overview, What is Data Mining and its Origin, Typical Data Mining Tasks, Data Mining Applications/Examples || [[file:Data Mining Unit 1.pdf]] ||  ||   ||
 * 2 || 10/02/10 || Wednesday || Structured vs. Non-structured Data, SQL and OLAP vs. Data Mining, Data Types, Normalization Techniques, Outlier Detection Methods, Dimensionality Reduction, Mean-Variance based Feature Ranking (Supervised) || [[file:Data Mining Unit 2.pdf]] ||  ||   ||
 * 3 || 17/02/10 || Wednesday || Entropy-based Feature Ranking (Unsupervised), Supervised and Unsupervised Feature Discretization || [[file:Data Mining Unit 3.pdf]] || Project # 1 ||  ||
 * 4 || 17/02/10 || Wednesday || Classification using Classification/Decision Trees, Splitting of Nodes: Binary vs. Multi-way, Splitting of Continuous Data, Measures of Node Impurity: GINI, Entropy and Misclassification Error || [[file:Data Mining Unit 4.pdf]] ||  ||   ||
 * 5 || 24/02/10 || Wednesday || Classification Tree (Cont'd), Working of Decision Tree Induction Algorithm ||  ||   ||   ||
 * 6 || 24/02/10 || Wednesday || Weka and KNIME Demos, Model Evaluation: Accuracy, Weighted Accuracy, Confusion Matrix, Recall and Precision || [[file:Data Mining Unit 5.pdf]] ||  ||   ||
 * 7 || 03/03/10 || Wednesday || ROC Curves and their computation, Gains and Lift Charts, Naive Bayes || [[file:Data Mining Unit 6.pdf]] ||  ||   ||
 * 8 || 03/03/10 || Wednesday || PAKDD 2009 Data Analysis using Weka and KNIME ||  ||   ||   ||
 * 9 || 06/03/10 || Saturday || Project # 1 Discussion ||  ||   ||   ||
 * 10 || 10/03/10 || Wednesday || Artificial Neuron Networks: History and Motivation, Perceptrons, Multi-layer Feedforward Networks and Backpropagation Algorithms || [[file:Data Mining Unit 7.pdf]] ||  ||   ||
 * || 17/03/10 ||  || **Midterm I** ||   ||   ||   ||
 * 11 || 20/03/10 || Saturday || Clustering: Basic Concepts and Popular Types, Applications, Similarity Functions, K-Means: Concepts, Working, Limitations, Schemes to Handle Initial Centroid Problems in K-Means || [[file:Data Mining Unit 8.pdf]] ||  ||   ||
 * 12 || 20/03/10 || Saturday || Schemes to Handle Initial Centroid Problems in K-Means, Hierarchical Clustering, Single/Complete/Average Linkages, Validity of Clusters ||  ||   ||   ||
 * 13 || 24/03/10 || Wednesday || Clustering (Cont'd) - Weka & KNIME Demos ||  ||   ||   ||
 * 14 || 27/03/10 || Saturday || ANN (Cont'd), Application of ANN in Test Efficiency of KSE || [[file:On Testing Efficiency of KSE using CI.pdf]] ||  ||   ||
 * 15 || 27/03/10 || Saturday || Two more Clustering Techniques: Adaptive Resonance Theory and Kohonen Self-Organizing Maps || [[file:Data Mining Unit 9.pdf]] ||  ||   ||
 * 16 || 31/03/10 || Wednesday || AML Data Migration and Exploration ||  ||   ||   ||
 * 17 || 03/04/10 || Wednesday || Clustering Options in Weka, Pentaho and SQL Server ||  || Comparison of Opensource DM Softwares [[file:10.1.1.98.7642.pdf]] ||   ||
 * 18 || 06/04/10 || Saturday || Literature Survey of AML ||  || [[file:Application of Cluster-Based Local Outlier Factor.pptx]] ||   ||
 * 19 || 13/04/10 || Saturday || Guest Lecture on AML By Nauman Sheikh ||  ||   ||   ||
 * 20 || 24/04/10 || Saturday || AML Data Cleaning, Pre-pocessing and Aggregation, Feature Selection ||  ||   ||   ||
 * 21 || 05/05/10 || Wednesday || Fuzzy c-Means, Clustering Options in SPSS Clementine and KNIME, || [[file:Data Mining Unit 10.pdf]] ||  ||   ||
 * 22 || 08/05/10 || Saturday || Association Rules Mining, Frequent Itemsets, Support & Confident, Apriori Algorithm || [[file:Data Mining Unit 11.pdf]] ||  ||   ||
 * 23 || 08/05/10 || Saturday || Association Rules (Cont'd), Interestingness Measures, Lift/Interest, Multidimensional data, Handling Categorical and Continuous Data, Min-Apriori, Multi-Level Association Rules ||  ||   ||   ||
 * 24 || 12/05/10 || Wednesday || Association Rules in Weka and SPSS Clementine, Introduction to Hypothesis Testing || [[file:Data Mining Unit 12.pdf]] ||  ||   ||
 * 25 || 19/05/10 || Wednesday || Introduction to Principal Component Analysis, Introduction to R Language ||  || [[file:principal_components.pdf]]
 * 26 || 22/05/10 || Saturday || Guest Lecture by Prof. Ahmad Raza on Principal Component Analysis ||  ||   ||   ||
 * 27 || 26/05/10 || Saturday || Principal Component Analysis (Cont't) - Computation of Eigen Values and Vectors, Comparison of Principal Components based on Covariance and Correlation Matrices || [[file:Data Mining Unit 13.pdf]] ||  ||   ||
 * 28 || 27/05/10 || Saturday || Presentations: Text Mining and Web Mining ||  ||   ||   ||