CLASS Product Vector

GitHub Repo https://github.com/Srikachu/VectorClassExercise

Srikachu/VectorClassExercise

Vector class: with scalar, dot and cross product, as well as magnitude

GitHub Repo https://github.com/shiro1307/Vector3D-mini-in-cpp

shiro1307/Vector3D-mini-in-cpp

Lightweight C++ Vec3 class supporting vector arithmetic, dot/cross products, normalization, projection, and angle calculations.

GitHub Repo https://github.com/syedazoobia/N-Dimensional-Vector

syedazoobia/N-Dimensional-Vector

java implementation of vector operations (addition, subtraction, dot product, cross product, cloning, and equality) with a custom Vector class.

GitHub Repo https://github.com/frknrnn/Covid19_classification_tmempr

frknrnn/Covid19_classification_tmempr

Medical images are crucial data sources for not easily diagnosed diseases. X-rays, one of the medical images, have high resolution. Processing high-resolution images leads to a few problems such as the difficulties in data storage, the computational load, and the time required to process high-dimensional data. It is a vital element to be able to diagnose diseases fast and accurately. In this study, a data set consisting of lung X-rays of patients with and without COVID-19 symptoms was taken into consideration and disease diagnosis from these images can be summarized in 2 steps as preprocessing and classification. Preprocessing step is the feature extraction process and in this step, the recently developed decomposition-based method Tridiagonal Matrix Enhanced Multivariance Products Representation (TMEMPR) is proposed as a feature extraction method. Classification of images is the second step where the Random Forest and Support Vector Machine (SVM) is applied as classifiers. Also, X-ray images have been reduced by 99,9\% with TMEMPR and with several state-of-the-art feature extraction methods which are Discrete Wavelet Transform (DWT), Discrete Cosine Transform(DCT) The results are examined under different feature extraction methods. It is observed that a higher accuracy rate of classification is achieved by using the TMEMPR method.

GitHub Repo https://github.com/enginaybey/VectorClass

enginaybey/VectorClass

Vector Class, Vector operations, Dot product

GitHub Repo https://github.com/orizion/prcpp_vector

orizion/prcpp_vector

A Vector Class with implementation for scalar product adding subtracting and multiplying

GitHub Repo https://github.com/wargod797/Support_Vector_Machine_Classification

wargod797/Support_Vector_Machine_Classification

Predicting the Product Purchase Through Social Media Ads, By age and Salary

GitHub Repo https://github.com/YouBM/vec2prod

YouBM/vec2prod

Class for converting parameters vector to product

GitHub Repo https://github.com/kshitizrohilla/user-purchase-prediction-and-classification-using-support-vector-machine-algorithm

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.

GitHub Repo https://github.com/jashbauer/Python-Vector_Class

jashbauer/Python-Vector_Class

Class that builds a vector from a list, defining several vector properties. Vector operations (sum, dot product and length of cross product) are also implemented.