Virtual University

Hierarchical Methods:DIANA (Divisive Analysis) (V-U)

Information Extraction (V-U)

Information gain (V-U)

Information Retrieval (V-U)

Introduction to rain forest (V-U)

Introduction, Motivation & Science Evolution History (V-U)

Introduction: A Multi-Dimensional View of Data Mining (V-U)

Introduction: Major Challenges& Issues in Data Mining (V-U)

Introduction: Patterns to mine (V-U)

Introduction: What Is Data Mining? (V-U)

Introduction: What Kind of Applications Are Targeted? (V-U)

Introduction: What Kind of Data Can Be Mined? (V-U)

Introduction: What Technology Are Used in data mining? (V-U)

Language model (V-U)

LM example (V-U)

Market basket analysis and its usages (V-U)

Measuring Data Similarity and Dissimilarity: Attributes of Mixed Type (V-U)

Markov assumption (V-U)

Measuring Data Similarity and Dissimilarity: Cosine Similarity (V-U)

Measuring Data Similarity and Dissimilarity: Data Matrix and Dissimilarity Matrix (V-U)

Measuring Data Similarity and Dissimilarity: Distance on Numeric Data (V-U)

Measuring Data Similarity and Dissimilarity: Introduction (V-U)

Measuring Data Similarity and Dissimilarity: Proximity Measure (V-U)

Measuring Data Similarity and Dissimilarity: Standardizing Numeric Data (V-U)

Model Evaluation and Selection: Accuracy, Error Rate, Sensitivity and Specificity using Evaluation matrix Matrix (V-U)