Data Mining Notes | Elective
Here is Data Mining Notes and Past Questions!
Notes
Chapter 1 & 2 Introduction & Data Preprocessing
Chapter 6 & 7 Anomaly/ Fraud Detection & Advanced Data Mining Application
Past Question
📊 What is Data Mining? | Learn with CaveStudy
Data Mining is the process of discovering patterns, trends, and useful information from large sets of data. It combines techniques from statistics, machine learning, and database systems to help extract meaningful insights.
🔍 Why is Data Mining Important?
In today’s data-driven world, organizations collect huge amounts of data. With data mining, they can:
- Make better decisions
- Predict customer behavior
- Detect fraud
- Improve business strategies
⚙️ Key Steps in Data Mining:
- Data Collection – Gather relevant data from various sources.
- Data Cleaning – Remove noise or irrelevant data.
- Pattern Discovery – Use algorithms to find patterns or relationships.
- Interpretation – Understand and apply the insights.
📘 Real-World Applications:
- E-commerce: Recommending products
- Healthcare: Diagnosing diseases
- Finance: Credit scoring and risk analysis
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