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Discover how data mining techniques drive business success. From revealing patterns to forecasting results, it revolutionizes operations. View our presentation for a concise overview. Visit - https://bit.ly/42BI17Y
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DATA MINING And its Techniques
Introduction to Data Mining • Definition: Data mining is the process of extracting knowledge or insights from massive amounts of data through statistical and computational techniques. • Objective: Finding hidden patterns and relationships in data to make predictions or informed decisions. • Importance: Enables companies to gain insights into clientele, improve revenue, reduce costs, and develop effective marketing strategies.
How Data Mining Works • Process: Examining and evaluating big data blocks to find significant patterns and trends. • Applications: Fraud detection, credit risk management, spam filtering, market research, etc. • Steps: • Data Gathering and Loading • Data Organization and Planning • Custom Application Software Utilization
Data Mining Techniques • Association Rules • Classification • Clustering • Decision Trees • K-Nearest Neighbor (KNN) • Neural Networks • Predictive Analysis
Data Mining Process • Understand the Business • Understand the Data • Prepare the Data • Build the Model • Evaluate the Results • Implement Change and Monitor
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