Unit 1: Introduction
Unit 2: Data Preprocessing
Unit 3: Classification
Unit 4: Association Analysis
Unit 5: Cluster Analysis
Unit 6: Information Privacy and Data Mining
Unit 7: Advanced Applications
Unit 8: Search Engines
Unit 9: Data Warehousing
Unit 10: Capacity Planning
Additional PDF Notes TU Old Paper Solution Data Mining - Questions Bank
Intro Data Mining Origin Data Preprocessing Classification and Prediction Basics Classification Decision Trees Rule Based Classifier Classification: KNN Bayesian Classifier ANN Classifier Issues: Overfitting, Validation Model Comparison Association Rules: Apriori Principle Association Rules: FP-Growth Handling Categorical Attributes Cluster Analysis Information Privacy and Data Mining Advanced Application and Search Engines Capacity Planning
Additional PDF Notes TU Old Paper Solution Data Mining - Questions Bank
Intro Data Mining Origin Data Preprocessing Classification and Prediction Basics Classification Decision Trees Rule Based Classifier Classification: KNN Bayesian Classifier ANN Classifier Issues: Overfitting, Validation Model Comparison Association Rules: Apriori Principle Association Rules: FP-Growth Handling Categorical Attributes Cluster Analysis Information Privacy and Data Mining Advanced Application and Search Engines Capacity Planning
