Transparent and Interpretable Crop Yield Forecasting using XAI Techniques and Machine Learning Models

Name: Transparent and Interpretable Crop Yield Forecasting using XAI Techniques and Machine Learning Models
Creator: Ramesh V
Published: 2025-08-20T22:37:27.881Z
Keywords: Crop Yield

V, Ramesh; P, Kumaresan

doi:10.17632/28rkmzv9gb.1

Transparent and Interpretable Crop Yield Forecasting using XAI Techniques and Machine Learning Models

Published: 20 August 2025| Version 1 | DOI: 10.17632/28rkmzv9gb.1

Contributors:

Ramesh V,

Description

The historical agricultural yield data, encompasses records from 1997 to 2020, spanning 27 Indian states and 3 Union Territories. It comprises 19,689 instances, each described by ten distinct attributes. The dataset captures six agricultural seasons and includes data on 55 unique crop types cultivated across diverse agro-climatic regions of India

Transparent and Interpretable Crop Yield Forecasting using XAI Techniques and Machine Learning Models

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