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Implementation of Beyond Neural Scaling beating power laws for deep models and prototype-based models
ProtoTorch is a PyTorch-based Python toolbox for bleeding-edge research in prototype-based machine learning algorithms.
🧠 Java Machine-Learning framework for model training, evaluation, deployment, tuning and benchmarking!
Prototype based ML implementation for ascertaing the confidence of predicted labels from the Learning Vector Quantization family of advanced machine learning classification algorithms.
Saran Tani is a system developed to help farmers optimize their land resources to provide maximum productivity in agriculture.
A simple demo of LVQ4J usage on the Iris Data Set
Learning active instances on the border in the case of imbalanced data classification task.
This repository contains various networks implementation such as MLP, Hopfield, Kohonen, ART, LVQ1, Genetic algorithms, Adaboost and fuzzy-system, CNN with python.
SOM_PAK with LVQ_PAK: The Self-Organizing Map and Learning Vector Quantization Program Packages
machin inspection for pcb defects using computer vision and classifing it using neuralnetworks
Code for the paper Mutation Validation for Learning Vector Quantization.
Prototype-based Feature selection with the Nafes Package
Prototype-Based Soft Feature Selection Package
The Learning Vector Quantization 3 (LVQ 3) classification to digits data.
Classification methods applied to an imbalanced big dataset
LVQ (Learning Vector Quantization) library for Java
Master Thesis on Determining of Classification Label Security/Certainty
Prototype based ML implementation for Multiple reject thresholds for improving classification reliability
Basic Artificial Neural Network usage on BlackJack card game data with MATLAB
Model for water quality classification using Learning Vector Quantization algorithm. Dataset obtained from Kaggle, 8000 instance with 19 attribute and class labelled by safe and not safe
Building a Learning Vector Quantization 1 (LVQ1) network
Implementations of perceptron algorithm with 2 hidden layers, learning vector quantization, k-means clustering algorithm, for the course Computational Intelligence @uoi
Learning Vector Quantization ( or LVQ ) is a type of Artificial Neural Network which also inspired by biological models of neural systems. It is based on a prototype supervised learning classification algorithm and trained its network through a competitive learning algorithm similar to Self Organizing Map.
Depression Calculator as a Final Project for Datamining Subject in the College