Chapter wise Notes of Data Mining[Elective]

Data Mining is included among elective I subject for Bachelor’s degree in Computer and Electronics & Communication Enigneering with the view of getting students familiar with the fundamental principles, algorithms and applications of intelligent data processing and analysis and to provide an in depth understanding of various concepts and popular techniques used in the field of data mining.

The following chapter wise notes are based on IOE Syllabus of Data Mining. Go to respective link of Google Drive where you can read the notes online or download in PDF format for offline usage. Special thanks to Er. Pratap Sapkota from Himalaya College of Engineering(HCOE) for compiling the notes.

1. Chapter 1 & 2: The first two chapters of data mining includes introduction, origin and data warehousing basics and OLAP. Download notes of First and Second Chapter of data mining.
2. Chapter 3: It deals mainly with the classification algorithms, decision tree and rule based classifier. Bayesian and artificial neural network classifier is also included here. Download note of chapter 3 of data mining.
3. Chapter-4: Association-Analysis mainly concerns with Pattern & Apriori Principle and Subgraph, Infrequent Patterns. Get notes of chapter 4. Note of Cluster Analysis.
4. Chapter-5: This chapter focuses on clustering algorithms: K-means, Hierarchical, DBSCAN. Read note of Data Mining chapter 5 on Google Drive.
5. Chapter 6 & 7: The last two chapters has details of Anomaly & Fraud Detection along with web mining and multimedia.

Numericals & AI Algorithms You Must Learn

• PERFORMANCE METRICS CLASSIFICATION MODEL
• NAIVE BAYES ALGORITHM ALGORITHM & NUMERICAL
• DECISION TREE ALGORITHM & NUMERICAL
• KNN ALGORITHM & NUMERICAL
• KMEANS ALGORITHM & NUMERICAL
• PERFORMANCE METRICS: REGRESSION MODEL