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Classification and prediction in data mining

Classification is a technique of supervised learning in data mining. that technique is applied when the data patterns or samples are having some predefined pattern labels or class labels. the supervised learning algorithms first prepare the data models based on the existing patterns. these existing patterns are known as training samples. additionally the preparation of data models are known as the training of algorithms. after the training of algorithms the data model is used to recognize the similar newly appeared samples or patterns. that is a very essential and popular technique in data mining because for obtaining the precise outcomes these techniques are used. figure 1 classification There are two forms of data analysis that can be used for extract models describing important classes or predict future data trends. These two forms are as follows Classification Prediction These data analysis help us to provide a better understanding of large data. Classification predicts categorical and a prediction model predicts continuous valued functions. For example, we can build a classification model to categorize bank loan applications as either safe or risky, or a prediction model to predict the expenditures in dollars of potential customers on computer equipment given their income and occupation….