• SHAIK NAAZREEN SULTHANA
• Dr. K. VENKATA RAO

The tax plays a crucial role for the contributions of the country’s economy and its development. This research uses the data source as big data analysis due to the rapid growth of data in social media. In processing tax comments Facebook and Twitter were used as a source from which the data is derived. The results of opinions in the form of public sentiment in part of service, website system and news can be considered to improve the quality of tax services. In this paper, text mining is done through the various phases of text processing, feature selection and classification with Support Vector Machine (SVM), K-Nearest Neighbors (KNN) and Artificial Neural Network (ANN). The main purpose of this paper is to provide a comparison of some commonly used classification algorithms under same conditions. This type of comparison helps to provide the algorithms with more accurate result. The application of Artificial Neural Network (ANN) on Tax Comments which results prediction, is the main focus of this project. In doing so, we identify the learning methodologies utilized, data sources and specific challenges of predicting Tax Comments results. The predicted values for the classifiers were evaluated and the results were compared.

Machine-learning Techniques, Minmax Scalar, Data Mining, SVM, KNN, ANN

"Data Analysis and Feature Selection on Tax Comments Using Machine Learning Algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.426-431, June 2019, Available :http://www.jetir.org/papers/JETIR1907I50.pdf

"Data Analysis and Feature Selection on Tax Comments Using Machine Learning Algorithms", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp426-431, June 2019, Available at : http://www.jetir.org/papers/JETIR1907I50.pdf