Cost-Sensitive Learning / ReSampling / Weighting / Thresholding / BorderlineSMOTE / AdaCost / etc.

Theano implementation of Cost-Sensitive Deep Neural Networks

Value-driven and cost-sensitive analysis for scikit-learn

This repo contains implementation of advanced ML techniques. Includes model ensembles, cost-sensitive learning and dealing with class imbalance.

Pytorch implementation for paper 'BANNER: A Cost-Sensitive Contextualized Model for Bangla Named Entity Recognition'

A genetic algorithm based approach for cost sensitive learning, in which the misclassification cost is considered together with the cost of feature extraction.

Deep Cost-sensitive Kernel Machine Model - PAKDD 2020

Implementation of cost sensitive KNN algorithm described in Qin, et al, 2013

This work focuses on the development of machine learning models, in particular neural networks and SVM, where they can detect toxicity in comments. The topics we will be dealing with: a) Cost-sensitive learning, b) Class imbalance

A cost-sensitive BERT that handles the class imbalance for the task of biomedical NER.

Supplementary codes of the Master Thesis "Binary Classification on Imbalanced Datasets"

Credit Scoring Course: Module

Software implementation of a manuscript submitted to Information Sciences

WeLT TablERT-CNN Trainer