A machine-learning project to determine if a certain mushroom is edible or poisonous.

This repository shows the use of MLflow to track parameters, metrics and artifacts of a pipeline on a machine learning model.

Basic code for RBFN, MLP and KNN evaluated on the mushroom dataset.

This project implements a Naive Bayes Classifier from scratch using Python. The classifier is used to classify mushrooms as either edible or poisonous based on various features such as cap shape, cap color, gill color, etc.

An implementation of decision trees in R

mrdbid-p is the php mysql version of mrdbid.com - not assured of any future development

Tree Predictors for Binary Classification for Secondary Mushroom dataset

Proyecto de análisis y detección de hongos venenosos vs comestibles con ML.

This Machine Learning app classifies data using SVM, Logistic Regression and Random Forest presenting it in the form of a web app.

Mushroom Dataset Visualization

Apply machine-learning models on mushroom data to predict if a mushroom is edible or not