Performance Evaluation of K-Means Algorithm and Enhanced Mid-Point Based K-Means Algorithm on Mining Frequent Patterns

Provided by: International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Topic: Data Management
Format: PDF
Pattern and classification of stock data is very important for business development in decision making. Timely prediction of latest upcoming trends is also required in business. Clustering is used to generate groups of related patterns, while association provides a way to get generalized rules of dependent variables. Due to increase in the size and complexity of the data, it is impractical to manually analyze, explore, and understand the data. As a result, useful information is often overlooked.

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