GridSearchHelper 0.6.0

Advanced hyperparameter tuning using grid search for ML models

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GridSearchHelper

GridSearchHelper is a Python library designed to simplify hyperparameter tuning using Grid Search. It allows for automatic parameter grid generation and performs efficient grid search for machine learning models.

Installation

You can install GridSearchHelper from PyPI:

pip install GridSearchHelper
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# Hyperparameter Tuning for Classifiers

This project implements a hyperparameter tuning utility for multiple classifiers using `GridSearchCV` from `sklearn`. The supported classifiers include Random Forest, Gradient Boosting, AdaBoost, SVM, K-Nearest Neighbors, Logistic Regression, Decision Trees, Naive Bayes, MLP, and more.

## Features
- Grid search for hyperparameter optimization on a variety of models.
- Support for additional custom parameters.
- Cross-validation (CV) support for model evaluation.
- Parallel processing for faster results.

## Setup
1. Clone this repository:
   ``bash
   git clone https://github.com/alimovabdulla/GridSearchHelper.git
>>>>>>> 27a8174 (Updated project with new features)