An Overview of Machine Learning Techniques and Tools for Predictive Analytics

  • Darshan Labhade
  • Nikhil Lakare
  • Aniket Mohite
  • Siddhesh Bhavsar
  • Sushma Vispute
  • Govind Mahajan


Predictive analytics is the use of raw facts or data, algorithms of statistics and techniques of machine learning to identify what is the possibility of future outcomes based on historical data. Our main goal is to get the knowledge of what has happened in the past and predict future scenarios. This paper gives a brief introduction of various machine learning techniques and tools which use these machine learning techniques to accurately predict the outcomes based on the given data and business requirement. Furthermore, this paper is aimed help beginners in the field of predictive analytics to choose between various tools and techniques available in the market which can maximize the accuracy and outcomes.

Keywords: Prediction; Analytics; Machine Learning; Techniques; Tools; Data Mining;


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[1]Nishchol Mishra and Dr.Sanjay Silakari, “Predictive Analytics: A Survey, Trends, Application, Opportunities and Challenges,” International Journal of Computer Science and Information Technologies, Vol. 3 (3), 2012, 4434- 4438
[2]I.Rish, “An Empirical Study of Naïve Bayes Classifier”, IJCAI 2001 Empir Methods Artif Intell. 3.
[3]Sasan Karamizadeh, Shahidan M. Abdullah et al, “Advantages and Drawbacks of Support Vector Functionality,” 2014 IEEE 2014 International Conference on Computer, Communication, and Control Technology (I4CT 2014), September 2-4, Langkawi, Kedah, Malaysia.
[4]Jin Huang, Jingjing Lu and Charles X. Ling, “Comparing Naïve Bayes, Decision Trees, and SVM with AUC and Accuracy,” Proceedings of the Third IEEE International Conference on Data Mining (ICDM’03)0-7695-1978-4/03
[5]Arpit Bansal, Mayur Sharma, and Shalini Goel, “An Improved K-Means Clustering for Prediction Analysis using Classification Technique in Data Mining,” International Journal of Computer Applications (0975 – 8887) Volume 157 – No 6, January 2017
[6]Aderibigbe Israel Adekitan and Odunayo Salau, “The impact of engineering students’ performance in the first three years on their graduation result using educational data mining,” Heliyon 5 (2019) e01250
[7] S. R. Vispute, S. Kanthekar, A. Kadam, C. Kunte and P. Kadam, "Automatic Personalized Marathi Content Generation," 2014 International Conference on Circuits, Systems, Communication and Information Technology Applications (CSCITA), Mumbai, 2014, pp. 294-299.
[8] S. R. Vispute and M. A. Potey, "Automatic text categorization of marathi documents using clustering technique," 2013 15th International Conference on Advanced Computing Technologies (ICACT), Rajampet, 2013, pp. 1-5.
[9] S. R. Vispute, S. Patil, S. Sangale, A. Padwal and A. Ukarde, "Parallel Processing System for Marathi Content Generation," 2015 International Conference on Computing Communication Control and Automation, Pune, 2015, pp. 575-579.
[10] Sandeep Kumar, Deepak Kumar, and Rashid Ali, “Factor Analysis Using Two Stages Neural Network Architecture”, International Journal of Machine Learning and Computing, Vol. 2, No. 6, December 2012
[11] Abhay Kumar, Ramnish Sinha, Daya Shankar Verma, “Modeling using K-Means Clustering Algorithm”, 1st Int’l Conf. on Recent Advances in Information Technology | RAIT-2012 |
[12] J. Han and M. Kamber, “Data mining Concepts and techniques”, 2nd edition, Morgan Kaufmann Publishers, pp. 401-404, 2007.
[13] Stephen J. Redmond, Conor Heneghan, “A method for initialising the K-means clustering algorithm using kd-trees”, Pattern Recognition Letters 28 (2007) 965-973.
[14] O. Dekel, O. Shamir, and L. Xiao. Learning to classify with missing and corrupted features. Machine Learning, 81(2):149–178, 2010.
[15] M.Reza, F.Derakhshi, M.Ghaemi, "Classifying Different Feature Selection Algorithms Based on the Search Strategies", International Conference on Machine Learning, Electrical and Mechanical Engineering (ICMLEME'2014), Dubai (UAE)
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Labhade, D., Lakare, N., Mohite, A., Bhavsar, S., Vispute, S., & Mahajan, G. (2020). An Overview of Machine Learning Techniques and Tools for Predictive Analytics. Asian Journal For Convergence In Technology (AJCT) ISSN -2350-1146, 5(3), 63-66. Retrieved from