A multi-dimensional data model: 3D data cube representation (V-U)

A multi-dimensional data model: Data Warehouse Design (V-U)

A multi-dimensional data model: Data warehouse snowflake schema (V-U)

A multi-dimensional data model: Fact Constellation Schema (V-U)

A multi-dimensional data model: Measures of Data Cube (V-U)

A multi-dimensional data model: Typical OLAP Operations (V-U)

Bag of words model (V-U)

Basic Concepts of Classification: A Two-Step Process (V-U)

Basic Concepts of Classification: Introduction (V-U)

Basic Concepts of Classification: Supervised vs. Unsupervised Learning (V-U)

Basic Concepts of Cluster Analysis: Challenges of Clutering (V-U)

Basic Concepts of Cluster Analysis: Clustering Applications (V-U)

Basic Concepts of Cluster Analysis: Clustering as a Preprocessing Tool (V-U)

Basic Concepts of Cluster Analysis: Clustering criteria (V-U)

Basic Concepts of Cluster Analysis: Measure the Quality of Clustering (V-U)

Basic Concepts of Cluster Analysis: Quality: What Is Good Clustering? (V-U)

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

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

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

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

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

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

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

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

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