Now showing items 1-5 of 5
Extracting Meta Knowledge from Machine Learning and Data Mining Algorithm
Extracting meta-knowledge from real-world meta-data is a challenging task, which is a fundamental conceptual instrument for knowledge engineering and knowledge management. Meta-knowledge is a knowledge that learns to ...
Correlation-Based Feature Grouping with Decision Tree for Classifying High-Dimentional Imbalanced Data
Classifying high-dimensional imbalanced data is a big challenge in mining real-world big data. Existing algorithms are classifying the majority class instances and get the maximum classification accuracy and minority ...
Classification by Clustering (CbC): An Approach of Classifying Big Data based on Similarities
Data classification in supervised learning is the process of classifying data for data mining task that helps to analyses data for decision making. The objective of a classification model is to correctly predict the ...
A Hybrid Approach for Feature Subset Selection to Classify High-Dimensional Data
In this modern era, we need to deal with large dimension of data set every day. Be it on social media, business, medicine or gene expression there are thousands of millions data to be processed everyday. So dealing with ...
Scalable Decision Tree Induction For Mining Big Data
Big data mining is one of the major challenging research issues in the field of machine learning for data mining applications in this present digital era. Big data consists of 3V's: (1) volume - massive amount of data/ ...