Classification is often confused with another data mining technique, clustering. As we’ll see later on, both techniques offer stark differences for businesses. Outlier and Anomaly Detection ...

Same as CSCA 5512Same as CSCA 5512 Specialization: Data Mining Foundations and Practice Instructor: Dr. Qin (Christine) Lv, Associate Professor of Computer Science Prior knowledge needed: Familiarity ...

Various data mining techniques, such as classification, clustering, and predictive analysis, help in transforming raw data into actionable intelligence.

Data mining techniques have been widely used for extracting knowledge from large amounts of data. Monitoring deforestation is utmost important for the developing countries.

Step 1: Handling of incomplete data Incomplete data affects classification accuracy and hinders effective data mining. The following techniques are effective for working with incomplete data.

Predictive analytics, pattern recognition, and classification problems are not new. Long used in the financial services and insurance industries, predictive analytics is about using statistics, data ...

Prediction – Prediction is a data mining technique that is often used in combination with other data mining techniques. It involves analyzing trends, classification, pattern matching, and relation.