Python 3.7 version of David Barber's MATLAB BRMLtoolbox
-
Updated
Aug 18, 2018 - Python
Python 3.7 version of David Barber's MATLAB BRMLtoolbox
Verifying suitability of dysphonia measurements for diagnosis of Parkinson’s Disease using multiple supervised learning algorithms.
It consists of basic concepts of Machine-Learning with its algorithms.
Basic templates of codes for quick ML
Minimax Classification with 0-1 Loss and Performance Guarantees
I use a self-implemented Trust-Region-Method to solve the optimization problem and calculate the accuracy based on test data
Modified Cutting angle method based on 'Cutting angle method - a tool for constrained global optimization'
Another repository for trying out machine learning algorithms for classification
This is an experiment on text classification using different supervised learning classifiers and their variants conducted on the Reuters-21578 dataset. The aim is to evaluate the best performance for each of the classifiers by properly tuning the parameters of each classifier so that the least error is recorded during the classification.
Implementations of various Machine Learning Algorithms
Apply Supervised Learning Algorithms using Python to predict breast cancer, diabetes, etc.. diseases.
Final Research Project Data Structures & Algorithms
Learning about Machine Learning
Add a description, image, and links to the supervised-learning-algorithms topic page so that developers can more easily learn about it.
To associate your repository with the supervised-learning-algorithms topic, visit your repo's landing page and select "manage topics."