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

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

Theano implementation of Cost-Sensitive Deep Neural Networks

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

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

Deep Cost-sensitive Kernel Machine Model - PAKDD 2020

To solve two main issues in credit card fraud detection - skewness of the data and cost-sensitivity

Official code for our paper - "Melanoma classification from dermatoscopy images using knowledge distillation for highly imbalanced data".

Paper under review on "Multimedia Tools and Applications" journal.

Advanced Machine Learning Algorithms including Cost-Sensitive Learning, Class Imbalances, Multi-Label Data, Multi-Instance Learning, Active Learning, Multi-Relational Data Mining, Interpretability in Python using Scikit-Learn.

Gastrointestinal diseases classification using Contrastive and Cost-sensitive Learning

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

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

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 python class for making machine learning algorithms cost sensitive.

Most existing classification approaches assume the underlying training set is evenly distributed but many real-world classification problems have an imbalanced class distribution, such as rare disease identification, fraud detection, spam detection, churn prediction, electricity theft & pilferage etc.

Solution to the Data Mining Cup 2019 competition

Final project for Data Mining course (Uniba)

Repo contains scripts to perform data analysis on structure data. It also provides a comparison of various ML algorithms at different stages of data preparation.

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