• K. PORCHILAMBI
• Dr. P. SUMITRA

Agriculture is full of uncertainty due to climate change, ground water deficiency, rainfall and evolution of new pests. Crop yield prediction in agriculture is a very big dilemma and there is huge dataset where farmers find difficult to predict the yield and seed selection. In today’s situation due to increase in the population the production of grains and agricultural products needs to be increased simultaneously to meet the demands of the people. Olden farming techniques need to be combined with the modern technology to enrich the results. Several Environment and economic factors like climate, rain and pesticide are unpredictable that affects the crop growth which in turn affects the productivity. Statistical and mathematical tools can be used to quantify the yield using past data. The result can assist farmers in crop choice and give an insight of the productivity that result in increased profit. Data set has been collected from Tamil Nadu and statistical websites for analysis and Machine learning algorithms and their role in agriculture were analyzed. This paper focus on the Machine learning algorithms like Naïve Bayesian, Support vector machine, Neural networks, Decision tree, K Nearest Neighbor in crop yield prediction.

Machine learning, K-Nearest neighbor, Naïve Bayes, Support Vector Machine, Decision tree, Regression tree.

"MACHINE LEARNING ALGORITHMS FOR CROP YIELD PREDICTION: A SURVEY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.112-116, March-2019, Available :http://www.jetir.org/papers/JETIRAQ06024.pdf

"MACHINE LEARNING ALGORITHMS FOR CROP YIELD PREDICTION: A SURVEY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp112-116, March-2019, Available at : http://www.jetir.org/papers/JETIRAQ06024.pdf