Fast Incremental Support Vector Data Description implemented in Python

The project aims at building a machine learning model that will be able to classify the various hand gestures used for fingerspelling in sign language. In this user independent model, classification machine learning algorithms are trained using a set of image data and testing is done. Various machine learning algorithms are applied on the datase…

A simple web app that helped students visualize the SVM algorithm according to their choice of hyperparameter setting.

Using Stanford CoreNLP and SVM-Rank in a Supervised Approach to Text Difficulty Ranking

Text mining and SVM training (mini-batch SGD with momentum)

svm classifier that will generate label by folder name

Reducing the Number of Training Samples for Fast Support Vector Machine Classification python implementation

Contains code involving CS 503 - Lab 3 : Implementation of Support vector Machine.

Predicts video game commercial success using training data and SVM.

This a very simple SVM Spam Emails Classification problem, I used Sklearn library to train the model and get better results

Hyperparameter tuning using a robust simulation optimization framework

Gender recognition system based on Support Vector Machine (SVM) and machine learning

A model I used (breast cancer dataset) to teach myself SVMs and learning more Scikit-learn w/ notes

"This program trains a model using 'SVM' or 'Softmax' and predicts the input data. Loss history and predicted tags are displayed as results."

SVM and Deep on MNIST Dataset.

To see if drivers were being profiled. I built a Support Vector Machine (SVM) classifier and a randomForest classifier to predict a driver's race given the traffic's stop's details. Successful classification will indicate the existence of bais in the traffic stops' data.