[Gretl-users] Initial Release of the KNN Package

Dear Gretl Community, I am happy to announce the initial release of the KNN (K-Nearest Neighbors) package for Gretl. This package introduces a comprehensive suite of tools for performing both (multi-class) classification and regression tasks using the KNN algorithm, directly within the Gretl environment. Key Features: - **Flexible Model Fitting**: Fit your KNN model using a variety of data splitting methods, including k-fold and leave-one-out cross-validation, as well as recursive and rolling window techniques. - **Standardization Support**: Automatically standardize features before model fitting, with separate standardization for training and test sets during cross-validation. - **Comprehensive Scoring**: Evaluate model performance with a range of metrics, including Precision, F-Score, and more, tailored to both classification and regression tasks. - **Optimal Neighbor Selection**: Utilize cross-validation to determine the optimal number of neighbors for your model, enhancing prediction accuracy. - **GUI interface**: Call the interface via the menu "Model -> Robust estimation --> KNN regression + classification" Getting Started: To install the KNN package, simply use the Gretl command interface or the GUI package manager. For detailed documentation on using the package, including function parameters and return values, please refer to the included help file. Happy Modeling, Artur