Data Mining - Part 1-II

Introduction

  • ?What is Data Mining
  • Motivating Challenges
  • The Origins of Data Mining
  • Data Mining Tasks

Data

  • Types of Data
  • Data Quality
  • Data Processing
  • Measures of Similarity and Dissimilarity

Exploring Data

  • The Iris Data Set
  • Summary Statistics
  • Visualization
  • OLAP and Multidimensional Data Analysis

Classification

  • Preliminaries
  • General Approach to Solving a Classification Problem
  • Decision Tree Induction
  • Model Overfitting

Association Analysis: Basic Concepts and Algorithms

  • Problem Definition
  • Frequent Itemset Generation
  • Rule Generation
  • Compact Representation of Frequent Itemset

Cluster Analysis: Basic Concepts and Algorithms

  • Overview
  • K-means
  • Agglomerative Hierarchical Clustering
  • DBSCAN

Anomaly Detection

  • Preliminaries
  • Statistical Approaches
  • Proximity-Based Outlier Detection
  • Density-Based Outlier Detection

Visualization and Visual Data Mining

  • Introduction
  • Parallel Coordinate
  • Grand Tour
  • Applications of Visual Data Mining