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IJSTR >> Volume 9 - Issue 3, March 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Enhanced Gradient Boosting Regression Tree For Crop Yield Prediction

[Full Text]

 

AUTHOR(S)

K.Shyamala, I.Rajeshwari

 

KEYWORDS

Agriculture, Data Mining, Decision tree, Gradient Boosting, MAE, MSE, Yield prediction.

 

ABSTRACT

Agriculture, the main occupation and backbone of our country, is one of the most important fields in the emerging real world and is in poor condition due to the lack of proper guidance to the farmers. This work presents an approach which uses modified gradient boosting regression technique to predict the yield of the crops to be cultivated based on the weather condition and the season. This is done by applying different statistical techniques in computing the minimum weight of the leaf, minimum samples for split and least squares error. The dataset has been collected from the publicly available Indian Government Records. From the dataset, two datasets of size 2000 and 4000 are formed. The original and modified algorithm were compared based on the metrics accuracy on training set, accuracy on test set, mean accuracy and standard deviation, MAE (Mean Absolute Error), MSE(Mean Squared Error) and R squared score by applying them on two datasets. The modified algorithm shows a better result.

 

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