Data Mining is a technique that attempts to find useful pattern from substantial volume of data. The paper reviews data mining and its techniques in e- governance. The paper also reviews the influence of the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) on the rural India. The objective of MGNREGA is to provide at least hundred days of job to the rural and tribal population, whose living entirely depends on daily wages. Moreover the paper gives the relative evaluation of numerous data mining methods and algorithms.

Data Mining, MGNREGA, Data Mining Techniques

[1]. Hardik Gohel, “Looking Back at the Evolution of the Internet”, CSI Communications - Knowledge Digest for IT Community, Vol.38, Issye.6, pp. 23-26, 2015.
[2]. Nikita Jain, Vishal Shrivastava , “Data Mining Techniques: A Survey Paper”, International Journal of Research in Engineering and Technology, Vol.2, Issue.11, pp.2319-1163, 2013.
[3]. AKB. Kote, “role of mahatma gandhi national rural employment guarantee programme inrural –urban migration -a gram panchayat village level study in gulbarga districtof karnataka state”, Journal of Global Economy, Vol.7, Issue.4, pp.275-291, 2011.
[4]. P. Sumithra, VV. Kumari, “Performance Analysis of MGNREG Scheme using Classification”, International Journal of Science and Research, Vol.4 ,Issue.10, pp.223-226, 2015.
[5]. Dr.M.Usha Rani, “Analysis on Households Registered/Working through Data Mining Techniques on NREGS (National Rural Employment Guarantee Scheme) Data of Andhra Pradesh”, International Journal of Engineering and Innovative Technology (IJEIT), Vol.2, Issue.2, pp.1-10, 2012.
[6]. T. Smitha, V. Sundaram. , “Comparative Study Of Data Mining Algorithms For High Dimensional Data Analysis”, International Journal of Advances in Engineering & Technology, Vol.2, Issue.4, pp.44-52, 2012.
[7]. Sumit Garg , AK. Sharma, “Comparative Analysis of Data Mining Techniques on Educational Dataset”, International Journal of Computer Applications, Vol.74, No.5, pp.1-7, 2013.
[8]. Dr.M.Usha Rani, “Expenditure Analysis Through Data Mining Techniques on NREGS(National Rural Employment Guarantee Scheme) Data of Andhra Pradesh”, IRACST – Engineering Science and Technology: An International Journal, Vol.2, No. 4, pp.122-129, 2012.
[9]. G. Sugapriyan, S. Prakasam, “Analyzing the Performance of MGNREGA Scheme using Data Mining Technique”, International Journal of Computer Applications, Vol.109, No.9, pp.123-127, 2015.
[10]. Lavannya Varghese, Christina Joseph, Vince Paul, “Survey on Mining Educational Data and Recommending Best Engineering College”, International Journal of Science, Engineering and Computer Technology, Vol.6, Issue.1, 66-69, 2016.
[11]. Moksha Shridhar, Mahesh Parmar, “Survey on Association Rule Mining and Its Application”, International Journal of Computer Science and Engineering, Vol.5, Issue.3,pp.129-135, 2017.
[12]. Mala Bharti, Vineet Richhariya, Mahesh Parmar, “An Implementation of IDS in a Hybrid Approach and KDD CUP Dataset”, International Journal of Research Granthaalayah (IJRG) Indore, Dec-14, Vol. 2, Issue.2, pp. 2-12, 2014
[13]. Mala Bharti, Vineet Richhariya, Mahesh Parmar, “A Survey on Data Mining based Intrusion Detection Systems”, International Journal of Computer Networks and Communications Security, Vol. 2, No.12, pp. 485-490, 2014.
[14]. NA. Shiekh, MA. Mir, “Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA): A Right Based Initiative towards Poverty Alleviation through Employment Generation", International Journal of Science and Research (IJSR), Vol.5 Issue.1, pp.1344-1348, 2016.
[15]. P. Chakraborty, “Evaluation of National Rural Employment Guarantee Act in Tamil Nadu”, Indian Institute of Technology, Madras, pp.1-29, 2010.
[16]. M. Dey, S.S. Rautaray, "Disease Predication of Cardio- Vascular Diseases, Diabetes and Malignancy in Lungs Based on Data Mining Classification Techniques", International Journal of Computer Sciences and Engineering, Vol.2, Issue.4, pp.82-98, 2014.
[17]. Bhavesh Patankar, Vijay Chavda, “A Comparative Study of Decision Tree, Naïve Bayesian and k-nn Classifiers in Data Mining”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol.4, Issue.12, pp.24-31, 2014.