This code performs classification using three different classification algorithms, namely Naive Bayes, Decision Tree, and K-Nearest Neighbors (KNN), on a red wine dataset. Here are the explanations of ...

This repository contains implementations of various classification algorithms using both traditional machine learning (ML) and deep learning (DL) techniques. Each model is implemented in Python using ...

The weighted k-NN classification algorithm has received increased attention recently for two reasons. First, by using neural autoencoding, k-NN can deal with mixed numeric and non-numeric predictor ...

Machine learning algorithms in Python are considered the spine of present-day artificial intelligence because they go beyond classical programming techniques and are able to perform innovative and ...

Decision Trees: A decision tree is built by repeatedly asking questions about the partition data. A decision tree falls under supervised Machine Learning Algorithms in Python and comes of use for both ...

The k-nearest neighbors (k-NN) algorithm is a technique for machine learning classification. The k-NN technique can be used for binary classification (predict where there are exactly two possible ...