Classifying malignant and benign tumors using Neural Networks 🔬
- Updated
Jun 4, 2021 - MATLAB
Classifying malignant and benign tumors using Neural Networks 🔬
Matlab code for Time Series Domain Adaptation Problems
A Novel Feature Fusion Approach for VHR Remote Sensing Image Classification
Artificial Intelligence assignments, for the course Artificial Intelligence : Knowledge Representation
Classification of cervical cancer using SVM is done on Herlev Pap Smear
A New Classification Method Using Soft Decision-Making Based on an Aggregation Operator of Fuzzy Parameterized Fuzzy Soft Matrices
MATLAB implementation of a decision tree based on ID3 capable of binary classification and handling of continuous features
This repository contains some machine learning projects as a practise on machine learning course on for Prof. Andrew Ng from Stanford University.
Safety regions research is a well-known task for ML and the main focus is to avoid false positives, i.e., including in the safe region unsafe points. In this repository, two methods for the research of zero FPR regions are proposed: the first one is based simply on the reduction of the SVDD radius until only safe points are enclosed in the SVDD …
ML Mini-Projects, in the context of Andrew's Ng course. Implemented in Octave.
classify emotion from speech signal
Tensor Singular Spectral Analysis for 3D feature extraction in hyperspectral images, TGRS, 2023
Function Approximation and Classification implementations using Neural Network Toolbox in MATLAB. Function Approximation was done on California Housing data-set and Classification was done on SPAM email classification data-set.
Fisher Linear Discriminant Analysis (FLD) Application
This repo is created to work on ML and 5G PoC
Matlab based Ph.D. project T-DTS, developed during for the thesis 2006-2009. It's the enhanced version of Tree-like Divide to Simplify (T-DTS) ANN (AI/ML) structure-based tool used for classification tasks. The credits: the v.1.0 was developed by Dr. M. Rybnik under supervision of Prof. K. Madani
Machine learning algorithms in Octave
Stanford's Machine Learning MOOC from
Machine Learning Assignments
An online course on ML taught by Andrew Ng. Introduces algorithms from scratch including regression models, classification, Neural Networks, SVMs, K-Means clustering, and applications such as Photo OCR.
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