wine_predictor
About Full Stack, End-to-End Machine Learning project that predicts wine success(based on sommelier's rating), from certain attributes, like alcohol content, acidity, etc. Based off of https://elitedatascience.com/python-machine-learning-tutorial-scikit-learn. This program encorpaorates data cleaning and preprocessing, hyperparameter tuning, and predcition.
The model is a random forrest regressor, and uses Random Grid Search to find a suitable list of hyperparamters. Then normal grid searching to fine-tune a narrow class of hyperparameters based on the random search.
Tuning can still be done, but as of now, an MSE of 0.380 was acheived, with a accuracy of 92.86% on the test set.
To Run:
- Clone this repo. it contains the main.py program, as well as the datasheet wine-quality.csv
- Either run main.py in a terminal, or load it into an IDE and run it. #) The program will run the grid searches and output the predictions.