Accuracy Estimation of Classification Algorithms with DEMP Model

Abstract: Data Mining is the extraction of hidden information from large databases. It is a technology with great potential to help organizations focus on the most important information in their data warehouses or database. Decision making with data mining is huge and complex task. In our work, we collected data from UCI repository and then apply five different classification methods for classifying different types of data based on their size. We compare these algorithms of classification and check which algorithm is optimal. By this task we extract knowledge that describes algorithms’ performance in various dataset. This work helps in making decision about the accuracy of classification algorithms.

Keywords: Data Mining, accuracy, classification algorithms, datasets.