A python class for making machine learning algorithms cost sensitive.
-
Updated
Apr 20, 2021
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"
Proposed assignment notebooks for Advanced Topics in Machine Learning tasks
R package for dealing with cost-sensitive learning (class imbalance and classification error cost) in a multiclass setting using lasso regularized logistic regression and gradient boosted decision trees.
Dementia Prediction by Khalil El Asmar, Fatima Abu Salem, Hiyam Ghannam, Roaa Al-Feel
Credit Scoring Course: Module
Software implementation of a manuscript submitted to Information Sciences
Fall 2020 - Computational Medicine - course project
A python implementation of a genetic algorithm based approach for cost sensitive learning
Software to build Decision Trees for imbalanced data. To cite this Original Software Publication: https://www.sciencedirect.com/science/article/pii/S2352711021001242
Cost Sensitive Learning in German Credit Data
Noise Identification, Noise reduction, and Sentiment Analysis on Bangla Noisy Texts
Predicting whether an African country will be in recession or not with advanced machine learning techniques involving class imbalance, cost-sensitive learning and explainable machine learning
Weka implementation of the cost-sensitive decision forest algorithm CSForest.
Gastrointestinal disease classification using Contrastive and Cost-sensitive Learning
This repository includes the analysis and report of a machine learning study created for an international academic conference IPCMC 2022.
Add a description, image, and links to the cost-sensitive-learning topic page so that developers can more easily learn about it.
To associate your repository with the cost-sensitive-learning topic, visit your repo's landing page and select "manage topics."