In the food industry, it is critical to know whether a mushroom is safe to be eaten or not. A machine learning algorithm will be implemented to predict whether a mushroom is safe to be eaten (edible) or not (poisonous). This will require to follow some specific machine learning stages like collecting and preprocessing data, choosing, training and evaluating a model, per- forming parameter tuning as well as making predictions. The model that has been chosen to move forward with is Logistic Regression for completing our classification task. An accuracy score of almost 97% was achieved using optimisers like GridSearchCV and a pipeline.
git clone https://github.com/pedroandreou/MushroomClassification.git
Run the Project in PyCharm IDE or Spyder IDE
