Investigation of effect of reducing dataset's size on classification algorithms

摘要: Data mining is now one of the most active field research. Extracting those nuggets information becoming crucial and its important technique classification. It helps to group data in some predefined classes. Various techniques for classification exists which classifies using different algorithms. Each algorithm has own area best worst performance. This paper concentrates on four famous algorithms, i.e., Decision Tree, Naive Bayes, K Nearest Neighbour Genetic Programming effect their performance time accuracy when number instances are incrementally decreased. will also investigate difference result working with binary class or multiclass datasets suggest algorithms follow certain kind dataset.