Groundnut Crop Yield Prediction Using Machine Learning Techniques
Keywords:
Crop analysis; Yield prediction; K-means; K-NN; Multiple Linear regressionAbstract
Yield prediction is a very important agricultural problem. Any farmer is interested in knowing how much yield he is about to expect. In the past, yield prediction was performed by considering farmer's experience on particular field and crop. Based on previous data, we can predict crop yield using machine-learning technique. Crop yield prediction is an important area of research, which helps in ensuring food security all around the world. We analyzed result of multiple linear Regression, Regression Tree, K-nearest Neighbor and Artificial Neural Network on Groundnut data of previous 8 years. We have done prediction based on Soil, Environmental and Abiotic attributes. KNN algorithm gives better result compared to other algorithms for Groundnut crop yield prediction.
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