Data Minning

Branches are used to represent choices with associated risks, costs, results, or probabilities. Rule induction is a way of deriving a set of rules to classify cases (Two Crows). These set of rules differ from those in a decision tree in that they are independent from one another. Boosting is a technique in which multiple random samples of data are taken and a classification model for each set of data is made (Two Crows). The genetic algorithm is a model of machine learning, whose behavior is based on the processes of evolution in nature. Populations of data are resented by chromosomes and then go through a process of evolution. The members of one set of data compete to pass on their most favorable characteristics to the next generation of data. This process continues until the best data is found. Many of the models and algorithms used in data mining are simplifications of the linear regression model.
             Data Mining is largely, if not entirely used for business purposes. The highest users of data mining include banking, financial, and telecommunications industries (Two Crows).
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             A survey taken by Two Crows Corporation turned up these applications of data mining:.
             Ad revenue forecasting .
             Churn (turnover) management .
             Claims processing .
             Credit risk analysis .
             Cross-marketing .
             Customer profiling .
             Customer retention .
             Electronic commerce .
             Exception reports .
             Food-service menu analysis .
             Fraud detection .
             Government policy setting .
             Hiring profiles .
             Market basket analysis .
             Medical management .
             Member enrollment .
             New product development .
             Pharmaceutical research .
             Process control .
             Quality control .
             Shelf management/store management .
             Student recruiting and retention .
             Targeted marketing .
             Warranty analysis .
             Data mining will have a different effect on different industries in the business world. In the telecommunications industry, for example, in order to retain or build market share and expand or develop new products and services, service providers will have to make the necessary adaptations and changes that the industry and pace setting technology requires.