This project is for classification of emotions using EEG signals recorded in the DEAP dataset to achieve high accuracy score using machine learning algorithms such as Support vector machine and K - Nearest Neighbor.

A simple implementation of a (linear) Support Vector Machine model in python. The classifier is an object of the SVC class which was imported from sklearn.svm library.

In this project, the performance of speech emotion recognition is compared between two methods (SVM vs Bi-LSTM RNN).Conventional classifiers that uses machine learning algorithms has been used for decades in recognizing emotions from speech.

Support Vector Machines with Python and Scikit-Learn - Support Vector Machines with Python and Scikit-Learn.ipynb

This project implements the Support Vector Machine (SVM) algorithm for predicting user purchase classification. It utilizes the user-data.csv dataset, which contains information about users and their purchase behavior.

Python implementation of Support Vector Machine (SVM) classifier - cperales/SupportVectorMachine

an image classification project using hog and svm from scratch - lcminhbu/hog_svm

Brain Tumor Detection: SVM-based image classification project. Includes data prep, PCA, SVM training, and evaluation metrics. Visualization of predictions and ROC curve analysis. #ML #ImageClassification - Neuro-Ghost/Brain-Tumor-Detection-ML

The project demonstrates how an SVM model can successfully identify and classify image of all the alphabets. - S-B-Iqbal/Image-Classification-using-SVM

qlearning random-forest tensorflow ... actor-critic trpo ppo ... An Architecture Combining Convolutional Neural Network (CNN) and Linear Support Vector Machine (SVM) for Image Classification...

Classification Using SVM in Python. Contribute to SnehaShukla937/SupportVectorMachine development by creating an account on GitHub.

Iris flower classification with kernel svm. machine-learning sklearn python3 classification kernel-svm-classifier

In this project, the L2-SVM variant of SVM was used as it is differentiable, and it provides a more stable result than the L1-SVM. For this implementation, the SVM was written using Python and TensorFlow (as the machine intelligence library), and the problem tackled is a binary classification of breast cancer using the Wisconsin diagnostic dataset.

Image Classification using SVM. Contribute to CheshtaK/Image-Classification development by creating an account on GitHub.

June 28, 2017 - -data_extraction.py: The data ... -SVMClassifier.py: implements the Linear SVC SVM Classifier and returns a list of classified output labels for the test data -corpus.txt: This is the corpus that is used for the project, this file can be stored ...

machine-learning random-forest ...sification performance-measurements ... This project implements the Support Vector Machine (SVM) algorithm for predicting user purchase classification....

In this project, I try to classify a pulsar star as legitimate or spurious pulsar star. The legitimate pulsar stars form a minority positive class and spurious pulsar stars form the majority negative class. I implement Support Vector Machines (SVMs) classification algorithm with Python and Scikit-Learn to solve this problem.

Using Tensorflow and a Support Vector Machine to Create an Image Classifications Engine - snatch59/cnn-svm-classifier

This repository contains Python code for image classification using the Support Vector Machine (SVM) algorithm. The project focuses on differentiating between "Infected" and "Healthy" images.

Support Vector Machine (SVM) Classification project with data preprocessing, feature engineering, and model evaluation on structured data, focusing on accuracy and model performance. - pragati-chat...