Components of Educational Data Mining

Data mining has come of age. Data mining took its birth from the data which is accumulated in hundreds of thousands to millions of customer information at one location which has guaranteed consistent access and consistent storage: the data warehouse. the metaphors between data warehouse and data mining can be confusing. the philosophy that ties these two together is the data repository presented to data mining tools. Data warehousing helps you build 'data mountains', where as Data mining helps you to extract essential and vital information by building cubes, data marts from these 'data mountains' that is useful to your areas of interest.

Some of the Data Mining Algorithms includes: 

a. Knowledge Discovery

              i. Decision Trees

                        a. CART (Classification & Regression Trees)

                        b. CHAID (Chi Square Automated Initialization Decision Tree)

                 ii. Neural Networks

b. Prediction

                i. Nearest Neighbor & K-nearest neighbor

               ii. Clustering
c. Genetic Algorithms

Selecting the right data mining algorithm depending upon Model structure, Search and retrieval method and Validation requirements of the situation.