Enhanced Classification Accuracy on Naive Bayes Data Mining Models

Provided by: International Journal of Computer Applications
Topic: Data Management
Format: PDF
A classification paradigm is a data mining framework containing all the concepts extracted from the training dataset to differentiate one class from other classes existed in data. The primary goal of the classification frameworks is to provide a better result in terms of accuracy. However, in most of the cases users cannot get better accuracy particularly for huge dataset and dataset with several groups of data. When a classification framework considers whole dataset for training then the algorithm may become unusable because dataset consists of several group of data.

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