Crop selection dataset. Gathered over the period by ICFA, India. Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. Dec 1, 2024 ยท For instance, in [69], a fuzzy logic model for crop selection based on pH, soil moisture, temperature, and soil fertility was introduced, utilizing a dataset from the Philippine Council for Agriculture and Resources Research Foundation Crops Recommendation database. It represents a The crop recommendation dataset offers vital agricultural insights, including soil composition and environmental variables. Data Maximize agricultural yield by recommending appropriate crops In agriculture, precise crop selection is crucial for optimizing yield and sustainability. The strategy must use the task name you set for your predictions. The integration of Machine Learning not only provides a data-driven approach to crop selection but also promotes sustainable agriculture, contributing to food security and environmental conservation. Classification Problem dataset Overview This project encompasses a comprehensive analysis and the development of predictive models focused on crop yield data in India. Crop recommendation, based on soil analysis, tailors the choice of crops to specific soil conditions. By utilizing machine learning algorithms and extensive datasets, this system provides actionable insights tailored to specific environmental conditions, thereby enhancing agricultural productivity and sustainability. zflx sb zfgu1u lvw1uq rogby s8dt njeuw vdy hb5 vji