The data was collected through a survey conducted across multiple districts in India. It consists of a variety of factors that could potentially impact the yield of rice crops. These factors include things like the type and amount of fertilizers used, the quantity of seedlings planted, methods of preparing the land, different irrigation techniques employed, among other features. The dataset comprises more than 5000 data points, each having more than 40 features.

For evaluating the performance of predictive models, the dataset has been split into a training set and a test set. About 25% of the data is reserved for testing. Within this test set, there is a further division into a public subset and a private subset. This split follows a 25:75 ratio, allowing for both a preliminary assessment of model performance and a later, more comprehensive evaluation.

Resource restriction: You may submit a maximum of 3 ensembled models.