GitHub topics: knearest-neighbors

Repositories

attcs/Octree

Octree/Quadtree/N-dimensional linear tree

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nadhif-royal/HeartDiseasePredictionML

This project aims to predict heart disease using machine learning models trained on clinical data. We explore different classification models to find the most effective approach. Models Used: Logistic Regression, K-Nearest Neighbors (KNN) (Best Performance: 97%), Random Forest

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Riciokzz/Spaceship-Titanic

Spaceship Titanic project.

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Sumair555/Email-Classification-Spam-or-Ham

The challenge is to accurately separate spam emails from regular ones using techniques from machine learning models.

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fs23yayan/MiniProject-kNearestNeighbors

Mini Project: k-Nearest Neighbors from Multiclass Classification dengan Algoritma Multinomial Naive Bayes dan k-Nearest Neighbors

Language: Python - Size: 1.95 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

mddragnev/k-nearest-neighbors

C++ implementation for machine learning algorithm K-NN

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rajaprerak/ML_DL_WebApp

Machine learning and Deep learning project

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LeweC/pose_tree

The PoseTree container is a data structure designed to efficiently perform K-NNS of poses. Especially poses where the orientation is given by Euler angles. Heavily based on the work of [@attcs] and their Octree library.

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RickyMiura/LoL-Match-Prediction

Predicting the outcomes of League of Legends matches using in-game event data and a KNN classifier.

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WalidAlsafadi/Titanic-Disaster

In this challenge, we ask you to build a predictive model that answers the question: “what sorts of people were more likely to survive?” using passenger data (ie name, age, gender, socio-economic class, etc).

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SpeedBird789/K-Nearest-Neighbours

This project was mainly on experimenting with different K values and finding the optimal value using the Elbow method. Refer to the screen recording attached below for a quick overview.

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Winterwind/HousingPricesProject

A two-part project involving making predictions using various regressors and then implementing linear regression from scratch and predicting that way

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Winterwind/ECG_Signal_Classification

Two-part project that involves detecting the R-peaks in an ECG signal to extract the individual ECG beats and making a machine learning model to classify them

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jio-gl/datahipsters

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.

Language: Python - Size: 4.04 MB - Last synced at: 10 months ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0

sharmeen-k/Image-Classifier-KNN

An image classification model using K Nearest Neighbours algorithm is implemented to differentiate between cats and dogs in an input image. The .yml file contains the trained model details created with CV Studio and a dataset of cat/dog images from IBM Object Storage.

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Dropout-Analytics/cuml_knn

Intro to k-nearest neighbors (KNN) with cuML.

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ammarsufyan/Coconut-Quality-Classification-Streamlit

This project is an application for classifying the quality of coconuts using the K Nearest Neighbors algorithm. It is built with Streamlit for easy deployment.

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Dhrumil-Zion/Predict-Price-of-Airlines-Industry

Data preprocessing of raw airline data and predicting prices through various different regression algorithms. Also dumping the model and reusing it for new data.

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saikrishnabudi/K-Nearest-Neighbour-KNN

Prepare a model for glass classification using KNN and Implement a KNN model to classify the animals in to categories.

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Sarvandani/ML_classifications-Sarcasm_detection

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

Language: Python - Size: 1.79 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

Paul-Andrew-15/ICC-2023-Worldcup-prediction

Predicting the champion of the 2023 Cricket World Cup through the implementation of the Random Forest algorithm.

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gtrunz/fruit_dataset

The purpose of this project is to promote understanding -- my own and others' -- of fundamental data science and machine learning concepts and tools. It currently consists of one notebook that classifies fruit types based on weight, volume, and image data.

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MarcVana/K-Nearest-Neighbors

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

Language: Python - Size: 129 KB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

mdsahilak/KNearestNeighbour

A swift implementation of a KNearestNeighbour Classifier in swift.

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satrapankti/Data-Science

Self Work Coding Files related to Data Science

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Z4ck404/recommender-system

Recommendation System Using K-Nearest Neighbors .

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pranshu1921/Microsoft-Malware-Detection

A multiclass classification problem to classify malware classes.

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Chandrakant817/Flight_Price-Prediction

Flight_Price Prediction using Machine Learning.(Regression Use Case)

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pranaymethuku/classical-ml

Implementing classical Machine Learning algorithms from scratch

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awiksshiith-narang/titanic_survivors

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

Language: Python - Size: 43 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

akhileshravi/KNearestNeighbours

This repository has a code (function) for K-Nearest Neighbours models. The model is tested on a dataset and compared with the slkearn KNN models. There is runtime analysis and accuracy analysis of the sklearn KNN models for classification and regression.

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oaarnikoivu/mnist

MNIST Digit Classification using an ANN, k-Nearest Neighbour and hybrid of the two.

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ms-daniel/II-Projeto-IA

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.

Language: Python - Size: 90.8 MB - Last synced at: 5 days ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

grvnair/heart-failure-prediction

Compared the metrics and performance of different classification algorithms on Heart Failure dataset from UCI ML Repository

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grvnair/knn-from-scratch

Created a Python program for K Nearest Neighbor Algorithm implementation from scratch. Determined the Euclidean distance between the data points to classify a new data point as per the maximum number of nearest neighbors. Implemented the algorithm on sklearn’s IRIS dataset which achieved an accuracy of 95.56%.

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