Algorithms

There are various data mining algorithms which can be used to build the mining model. But choosing the right algorithm for the right business task is critical. Different algorithms can be used to do the same business tasks but each algorithm produces different results.
The various types of algorithms are as follows:
1. Classification algorithm predicts one or more discrete variables, based on the other attributes in the dataset. eg: Microsoft Decision Trees Algorithm.

2. Regression algorithm predicts one or more continuous variables, such as profit or loss, based on other attributes in the dataset. eg: Microsoft Time Series Algorithm.

3. Segmentation algorithm divides data into groups, or clusters, of items that have similar properties. eg: Microsoft Clustering Algorithm.

4. Association algorithm finds correlations between different attributes in a dataset. The most common application of this kind of algorithm is for creating association rules, which can be used in a market basket analysis. eg: Microsoft Association Algorithm.

5. Sequence analysis algorithm summarizes frequent sequences or episodes in data, such as a Web path flow. eg: Microsoft Sequence Clustering Algorithm.

A data mining application can adopt different algorithms for different functions, for example we can use segmentation algorithms for exploring data and regression algorithms for prediction functionalities.

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