Abstract:Data mining and machine learning techniques help to predict suitable crops in ranking order for a given location with its soil nutrient status. We proposed a tuned bagging‐based K‐nearest neighbor ensemble label ranker and it is used to predict the ranked crops for density‐based spatial clustering of applications with noise (DBSCAN) based compressed crop‐ranked agricultural data. This ensemble integrates the commonly used Borda rank aggregation method, but there is a possibility to improve the performance of o… Show more
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