Crop Recommendation System using LightGBM with Analysis and Visualization

Abstract

An end-to-end crop recommendation system built on LightGBM, paired with rigorous EDA and visualization. The work demonstrates how gradient-boosted models perform on small, noisy agronomic datasets relative to classical ML baselines.