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Random Forest for Crop Yield Prediction by sipijjournal.aircc is a document available to read on EtoBox.
This study analyzes crop yield prediction in India from 1997 to 2020, focusing on various crops and key environmental factors including crop types and years, cropping seasons, specific details for each state, areas of cultivation, production quantities, annual rainfall, and the usage of fertilizers and pesticides. We applied advanced machine learning techniques like Logistic Regression, Decision Tree, KNN, Naïve Bayes, K-Mean Clustering, and Random Forest to predict agricultural yields.
- Author
- sipijjournal.aircc
- Language
- EN