support-vector-classifier
There are 110 repositories under support-vector-classifier topic.
harismuneer/Handwritten-Digits-Classification-Using-KNN-Multiclass_Perceptron-SVM
🏆 A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.
maximer-v/quantum-machine-learning
This is an exploration using synthetic data in CSV format to apply QML models for the sake of binary classification. You can find here three different approaches. Two with Qiskit (VQC and QK/SVC) and one with Pennylane (QVC).
howardyclo/NTHU-Machine-Learning
NTHU EE6550 Machine Learning slides and my code solutions for spring semester 2017.
Ruban2205/Iris_Classification
This repository contains the Iris Classification Machine Learning Project. Which is a comprehensive exploration of machine learning techniques applied to the classification of iris flowers into different species based on their physical characteristics.
shaadclt/Diabetic-Patient-Prediction
This project aims to predict diabetic patients using three different classification algorithms: Logistic Regression, Support Vector Classifier, and Random Forest Classifier. The project is implemented using Python and leverages scikit-learn, a popular machine learning library.
Ansu-John/Classification-Models
Build and evaluate various machine learning classification models using Python.
indrapaul824/Binary-Classification-Web-App
A web app for visualizing Binary Classification Results using Streamlit module in Python deployed on Heroku.
likarajo/premier_league
Predictions for the English Premier League season
rifatSDAS/satellite_machine_learning
Unsupervised and supervised learning for satellite image classification
shaadclt/Cancer-Classification-SupportVectorClassifier
This repository provides a cancer classification model using Support Vector Classifier (SVC). The model aims to classify cancer cases into benign or malignant based on various features obtained from medical examinations.
Jspano95/Retail-Customer-Classification-Modelling
Classification ML models for predicting customer outcomes (namely, whether they're likely to opt into email / catalog marketing) depending on customer demographics (age, proximity to store, gender, customer loyalty duration) as well as sales and shopping frequencies by department
kshitizrohilla/user-purchase-prediction-and-classification-using-support-vector-machine-algorithm
This project implements the Support Vector Machine (SVM) algorithm for predicting user purchase classification. The goal is to train an SVM classifier to predict whether a user will purchase a particular product or not.
SanjarH/Sarcasm-Detection
Project made in Jupyter Notebook with "News Headlines Dataset For Sarcasm Detection" from Kaggle.
absaw/trauma-data-analysis
Integrative Biomechanical and Clinical Features Predict In-Hospital Trauma Mortality
itsmarmot/Sentiment-Analysis
Sentiment Analysis is NLP technique used to determine the sentiment expressed in a piece of text, which can be positive, negative, or neutral. SVC is a powerful machine learning model that can be used for this purpose due to its effectiveness in handling high-dimensional data.
krish1919ls/machine_learning_models
Assignments from Applied Machine Learning Class (UTD BUAN-6341)
MatthewCSC/2020-Heart-Failure-Prediction
This repository contains a notebook that examines the performance of various classification models on the Kaggle dataset: https://www.kaggle.com/datasets/andrewmvd/heart-failure-clinical-data. The best performing model was a Random Forest Classifier with 86.67% accuracy.
ROCCYK/Classification
Intro to Machine Learning Assignment 2
ROCCYK/DiseasePredictor
Intro to Machine Learning Final Project
tboudart/Life-Expectancy-Regression-Analysis-and-Classification
I contributed to a group project using the Life Expectancy (WHO) dataset from Kaggle where I performed regression analysis to predict life expectancy and classification to classify countries as developed or developing. The project was completed in Python using the pandas, Matplotlib, NumPy, seaborn, scikit-learn, and statsmodels libraries. The regression models were fitted on the entire dataset, along with subsets for developed and developing countries. I tested ordinary least squares, lasso, ridge, and random forest regression models. Random forest regression performed the best on all three datasets and did not overfit the training set. The testing set R2 was .96 for the entire dataset and developing country subset. The developed country subset achieved an R2 of .8. I tested seven different classification algorithms to classify a country as developing or developed. The models obtained testing set balanced accuracies ranging from 86% - 99%. From best to worst, the models included gradient boosting, random forest, Adaptive Boosting (AdaBoost), decision tree, k-nearest neighbors, support-vector machines, and naive Bayes. I tuned all the models' hyperparameters. None of the models overfitted the training set.
Tekraj15/MLWebAppForBinaryClassificationOfMushroom
Interactive ML web application will allow users to choose classification algorithm, let them interactively set hyper-parameter values, and Input Image.
wesbarnett/spam-or-ham
Using a support vector machine to classify emails
adler-sudo/atac-seq-analysis
Visualize scATAC-seq profiles using PCA and UMAP. Construct a support vector classifier (SVC) to predict cell type given ATAC-seq expression profile.
amatov/SegmentationBiomarkerCTC
Our image analysis software performs segmentation of the cellular areas with cell surface expression of the prostate-specific membrane antigen to improve the precision of therapy and its customization
aryapangestu/Spada_Klasfikasi-Kualitas-Udara
Dari dataset tersebut akan mengklasifikasi kualitas pencemaran udara berdasarkan kategori perhitungan indeks standar pencemaran udara. Dimana dataset Indeks Standar Pencemaran Udara (ISPU) Tahun 2021 yang didapatan dari website Jakarta Open data dengan link: https://data.jakarta.go.id/dataset/indeks-standar-pencemaran-udara-ispu-tahun-2021
gaurav-bhadane/Diabetes_Predicton
A machine learning project to predict diabetes using a Support Vector Classifier model. It includes data preprocessing, model training, evaluation, and a Flask web application for real-time predictions.
lionelsamrat10/Iris-Flower-Prediction-Machine-Learning-Web-App
Created a web app, that predicts the type of flower using Iris Dataset by the University of California, Irvine
Neo-Panther/ML-Project-Predicting-Crime-Rate
ML Project implementing decision trees, boosting and svm classification from scratch.
NeonOstrich/Predicting-Autism-with-Machine-Learning
Development and comparison of 12 machine learning models to predict autism as well as a discussion of the process.
paschalugwu/alx-data_science-NLP
Empowering Advanced Text Classification and Wine Quality Prediction with Cutting-Edge Machine Learning Techniques.
psavarmattas/Stroke-Prediction-ML-Model
This is just a theoretical Machine Learning Model that will analyze the data and determine where the stroke can occur.
revanthchristober/Facial-Recognition-System
A Facial Recognition System using Python, OpenCV, Dlib. This project includes data preprocessing, face detection, feature extraction, and model training. Explore the LFW dataset, train a Support Vector Classifier, and implement real-time face recognition. Comprehensive notebooks and scripts guide each step.
sai-manas/Diabetes_Predictor_ML
Diabetes Predictor Web App Predict diabetes in patients using classification models such as Logistic Regression, Decision Tree, Naive Bayes, and Support Vector Machines. It is deployed in a Flask web application on AWS Elastic Beanstalk.
somenath203/Suicide-Depression-Predictor
Click below to checkout the website live
somjit101/Human-Activity-Recognition
This project is to build a model that predicts the human activities such as Walking, Walking Upstairs, Walking Downstairs, Sitting, Standing or Laying using readings from the sensors on a smartphone carried by the user.
sukruta230901/Machine-Learning-KNN-SVM-LAB
This repository contains the Lab practices of Machine Learning performed in Jupyter Notebook using python language. This repo consists of KNN and SVM Classification models to perform classification on the iris dataset.