• Tarun Kumar
• Rajiv Kumar

The registration Bureau of a country conducts study producing a gigantic dataset with a huge number of information focuses. The rich dataset contains itemized data about an individual's way of life including different information like his/her instruction foundation, work foundation, age, conjugal status and so on. These highlights change scarcely in an individual's life. The most every now and again changing element in an individual's life is his/her salary. Consistently individuals change occupations and get advancements which change the figures of their salary. This paper intends to foresee whether the pay of a person surpasses $50000/yr or not founded on statistics information gave by Census authority database, while considering different factors such as age, work class, gender, marital status, education, race, occupation etc. using exploratory analysis and classification algorithms. This investigation intends to utilize machine learning procedures in giving a response for the salary forecast. This model measures the accuracy of different machine learning models like Random forest classifier, Naïve Bayes classifier and Support vector classifier. The conclusions drawn might help in delivering wiser decisions. The result can be used for social purpose, commercial purpose and economic study of a region for level of economic inequality.

Income Prediction, Machine learning, Random forest classifier, Naïve Bayes classifier and Support Vector Classifier

"Intelligent Income prediction model", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 8, page no.660-669, August-2020, Available :http://www.jetir.org/papers/JETIR2008084.pdf

"Intelligent Income prediction model", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 8, page no. pp660-669, August-2020, Available at : http://www.jetir.org/papers/JETIR2008084.pdf