Data Mining (V-U)

Basic Concepts of Cluster Analysis: What is Cluster Analysis? (V-U)

Classification by Back propagation: A Multi-Layer Feed-Forward Neural Network (V-U)

Basic Concepts of Mining Frequent Patterns, Association and Correlation: : Closed Patterns and Max-Patterns (V-U)

Classification by Back propagation: Back propagation (V-U)

Basic Concepts of Mining Frequent Patterns, Association and Correlation: Why Is Freq. Pattern Mining Important? (V-U)

Classification by Back propagation: Defining a Network Topology (V-U)

Basic Concepts of Mining Frequent patterns: Introduction (V-U)

Classification by Back propagation: Introduction (V-U)

Basic Statistical Descriptions of Data: Box plot Analysis (V-U)

Classification by Back propagation: Neural Network as a Classifier (V-U)

Basic Statistical Descriptions of Data: Graphic Displays of Basic Statistical Descriptions using Histogram (V-U)

Classification issues (V-U)

Basic Statistical Descriptions of Data: Graphic Displays of Basic Statistical Descriptions using Quantile Plot (V-U)

Clustering data measures (V-U)

Basic Statistical Descriptions of Data: Graphic Displays of Basic Statistical Descriptions using Scatter plot (V-U)

Clustering High-Dimensional Data: CLIQUE (V-U)

Clustering High-Dimensional Data: Introduction (V-U)

Basic Statistical Descriptions of Data: Introduction (V-U)

Clustering High-Dimensional Data: The Curse of Dimensionality (V-U)

Clustering High-Dimensional Data:Why Subspace Clustering? (V-U)

Clustering matrixes (V-U)

Comparing classification methods (V-U)

Concept Hierarchy and its type (V-U)

Cyber Community (V-U)

Cyber Community Types (V-U)