It is a GUI based project where there are four datasets related to Rainfall, Yield, Temperature, and Pesticides. These datasets are used to predict the yield of the crop.
Various data preprocessing techniques are applied to the raw dataset. Regression models are performed on the dataset that is obtained after the preprocessing.
There are three regression techniques (KNN, Linear Regression using Gradient Descent, and Decision Tree) are implemented to predict the crop yield.
For every algorithm, the performance metrics are calculated to evaluate how well an algorithm is working for crop yield prediction.
The algorithm with the best performance metrics is used in the graphical user interface (GUI). This GUI will predict the crop yield when a user gives input values for the features provided in the GUI.
