Machine learning has been widely used in solving the problem of prediction and classification. It is also beneficial in the problem of tax avoidance detection. This study presents the utilization of machine learning classification approach for detecting tax avoidance of Malaysian government-linked companies (GLCs). There were nine machine learnings algorithms have been used on the real dataset collected from datastream and companies annual reports. The performance of these algorithms have been observed based on different training approaches and different features selection. The findings have revealed that the accuracy of results from each machine learnings were divergent according to the training approaches and features selection.
A New Epilepsy Identification Technique Based on VMD, RELIEFF Algorithm and Machine Learning Classification Approach
