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#
support-vector-classifier
Here are
123 public repositories
matching this topic...
🏆 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.
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).
NTHU EE6550 Machine Learning slides and my code solutions for spring semester 2017.
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.
Build and evaluate various machine learning classification models using Python.
👁 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.
Predictions for the English Premier League season
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.
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.
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 r…
Unsupervised and supervised learning for satellite image classification
Project made in Jupyter Notebook with "News Headlines Dataset For Sarcasm Detection" from Kaggle.
A web app for visualizing Binary Classification Results using Streamlit module in Python deployed on Heroku.
Assignments from Applied Machine Learning Class (UTD BUAN-6341)
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
Integrative Biomechanical and Clinical Features Predict In-Hospital Trauma Mortality
Loan Eligibility Prediction Model: A machine learning application to predict loan approval based on applicant data. Includes a web interface for submitting loan applications and receiving predictions. Built with Python and Jupyter Notebook.
Intro to Machine Learning Final Project
Intro to Machine Learning Assignment 2
Using a support vector machine to classify emails
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