Knn implementation without K parameter

An implementation of the K-Nearest Neighbors algorithm from scratch using the Python programming language.

A simple implementation of K Nearest Neighbors classifier model in python.

AU331机器学习与知识发现课程项目——拍照矩阵计算器开发

Building a ML model that can predicts the species of the flower from the measurements of the petal and the sepal

Esse pequeno projeto tem como objetivo fazer testes de acurácia com rede neural com apenas um neurônio sem classificadores e com 2 (dois) classificadores, sendo eles KNN e 1R.

Machine Learning Hyperparameter Optimization (Grid Search and Random Search)

Sklearn, logistic regression, Naive Bayes classifier, K-Nearest Neighbors, decision trees

DataHipsters is a service implementing MinHash similarity on a Key-Value Database (Google AppEngine/GCloud), including an API for k-nearest neighbors (k-nn) used in Online Recommender Systems.

A Python library of 'old school' machine learning methods such as linear regression, logistic regression, naive Bayes, k-nearest neighbors, decision trees, and support vector machines.

This is a repository to document my progress in learning the basics of common machine learning algorithms.

Simple KNN project based on an unlabeled dataset (created artificially).

This model predicts whether the survivors of the Titanic survived or not. In this file, different classification models are compared and predictions are done from the model(s) having highest accuracy. Here, 'training_data.csv' is used for training and testing the models and 'testing data.csv' is used for predictions. These data sets are from Kaggle