Now showing items 1-5 of 5
Big Data Mining in the Presence of Concept Drifting
Concept drift in big data mining is an absolute, highly demanding research issue in this digital era. A concept in "concept drift" involved in the field of data mining (DM) and machine learning (ML) studies is referred ...
Correlation Based Feature Selection with Clustering for Multi-Class Classification Tasks
In recent times high dimensional data is increasing rapidly. Reduce the dimensionality has become popular by feature selection process. So many scientists prefer to use correlation base feature selection method for grouping ...
Network Intrusion Classification with Feature Reduction
Nowadays, in data technology, data preservation has become a good issue. Computers and completely different security breaches are incessantly attacked by security threats. There are completely different malicious network ...
Active Learning with Clustering for Mining Big Data
Big data mining is become a key research issue nowadays. It's costly and also time-consuming to extract knowledge from big data. Big data is so big, it contains millions of data points that's why it's very difficult to ...
A Feature Group Weighting Method for Classifying High-Dimensional Big Data
Features hold the distinctive characteristics and intrinsic values of data. But it's of no use if the important information and pattern can not be extracted from the data coming from disparate sources and applications. ...