Data Mining is defined as the procedure of extracting information from huge sets of data. In other words, we can say that data mining is mining knowledge from data. The tutorial starts off with a basic overview and the terminologies involved in data mining and then gradually moves on to cover topics such as knowledge discovery, query language, classification and prediction, decision tree induction, cluster analysis, and how to mine the Web.
Data mining parameters include:
- Association – looking for patterns where one event is connected to another event
- Sequence or path analysis – looking for patterns where one event leads to another later event
- Classification – looking for new patterns (May result in a change in the way the data is organized but that’s ok)
- Clustering – finding and visually documenting groups of facts not previously known
- Forecasting – discovering patterns in data that can lead to reasonable predictions about the future (This area of data mining is known as predictive analytics.)
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