Revenue Prediction for Malaysian Federal Government Using Machine Learning Technique
- Computer Science2022 11th International Conference on Software and Computer Applications
After conducting several experiments, it is found that FFNN achieved highest accuracy, followed by random forest, and linear regression does not achieve good accuracy, thus it is considered as a not suitable method to be used on the federal government revenue dataset.
An application of machine learning on corporate tax avoidance detection model
- Computer Science, Business
The findings indicated that the machine learning models present better reliability with industry, governance and firm characteristics features rather than single year determinant mainly with the Random Forest and Logistic Regression algorithms.
Data Mining Techniques Applied in Tax Administrations: A Literature Review
- Computer Science2019 Sixth International Conference on eDemocracy & eGovernment (ICEDEG)
This study aims to present a literature review about the use of data mining techniques in tax administrations, identifying problems that could be resolved with data mining, limits that has been risen, results that have been obtained by applying data mining inTax administrations and techniques that have be used.
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Predicting Eshopping Data Using Deep Learning
- Computer Science
This paper shows how advanced Machine Learning algorithm and neural network algorithm combined successfully to obtain a high fraud coverage and also with a low false alarm rate.
A LINEAR REGRESSION APPROACH TO PREDICTION OF STOCK MARKET TRADING VOLUME: A CASE STUDY
- Computer Science
By applying linear regression for predicting behavior of S&P 500 index, it is proved that the proposed method has a similar and good performance in comparison to real volumes and the stockholders can invest confidentially based on that.