Treers / MetaCostLinks
P. Domingos proposed a principled method for making an arbitrary classifier cost-sensitive by wrapping a cost-minimizing procedure around it. The procedure, called MetaCost, treats the underlying classifier as a black box, requiring no knowledge of its functioning or change to it.
☆39Updated 6 years ago
Alternatives and similar repositories for MetaCost
Users that are interested in MetaCost are comparing it to the libraries listed below
Sorting:
- [ICDE'20] ⚖️ A general, efficient ensemble framework for imbalanced classification. | 泛用,高效,鲁棒的类别不平衡学习框架☆259Updated last year
- Cost-Sensitive Learning / ReSampling / Weighting / Thresholding / BorderlineSMOTE / AdaCost / etc.☆107Updated 4 years ago
- XGBoost for label-imbalanced data: XGBoost with weighted and focal loss functions☆327Updated last year
- [NeurIPS’20] ⚖️ Build powerful ensemble class-imbalanced learning models via meta-knowledge-powered resampler. | 设计元知识驱动的采样器解决类别不平衡问题☆109Updated last year
- Oversampling for imbalanced learning based on k-means and SMOTE☆127Updated 4 years ago
- ☆37Updated 4 years ago
- Our implementations of the Multi-class Imbalance learning algorithms (for the KBS paper)☆46Updated 6 years ago
- Ensemble learning related books, papers, videos, and toolboxes☆297Updated 5 years ago
- A python implementation of a genetic algorithm based approach for cost sensitive learning☆8Updated 5 years ago
- Python package for tackling multi-class imbalance problems. http://www.cs.put.poznan.pl/mlango/publications/multiimbalance/☆78Updated last year
- Python-based implementations of algorithms for learning on imbalanced data.☆239Updated 3 years ago
- Active semi-supervised clustering algorithms for scikit-learn☆101Updated 5 years ago
- 🛠️ Class-imbalanced Ensemble Learning Toolbox. | 类别不平衡/长尾机器学习库☆383Updated 3 months ago
- Feature Selection using Genetic Algorithm (DEAP Framework)☆370Updated 2 years ago
- Automating Outlier Detection via Meta-Learning (Code, API, and Contribution Instructions)☆181Updated 3 years ago
- A missing value imputation library based on machine learning. It's implementation missForest, simple edition of MICE(R pacakge), knn, EM,…☆107Updated last year
- Code and documentation for experiments in the TreeExplainer paper☆185Updated 5 years ago
- Feature Selection for Clustering☆96Updated 7 years ago
- Missing Data Imputation for Python☆244Updated last year
- A Particle Swarm Optimization (PSO) for Feature Selection. Using PySwarm.☆53Updated 7 years ago
- Python code to prune ensembles☆13Updated 3 years ago
- ☆15Updated 2 years ago
- An implementation of the focal loss to be used with LightGBM for binary and multi-class classification problems☆253Updated 5 years ago
- A collection of 85 minority oversampling techniques (SMOTE) for imbalanced learning with multi-class oversampling and model selection fea…☆668Updated last year
- Feature selection in neural networks☆239Updated 10 months ago
- pyCausalFS:A Python Library of Causality-based Feature Selection for Causal Structure Learning and Classification☆70Updated 4 years ago
- (Python, R) Cost-sensitive multiclass classification (Weighted-All-Pairs, Filter-Tree & others)☆48Updated 2 months ago
- Python3 binding to mRMR Feature Selection algorithm (currently not maintained)☆141Updated 7 months ago
- Houses implementation of the Fast Correlation-Based Filter (FCBF) feature selection method.☆61Updated 3 years ago
- Positive-unlabeled learning with Python.☆237Updated this week