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☆257Updated last year
- Oversampling for imbalanced learning based on k-means and SMOTE☆128Updated 4 years ago
- Cost-Sensitive Learning / ReSampling / Weighting / Thresholding / BorderlineSMOTE / AdaCost / etc.☆109Updated 4 years ago
- XGBoost for label-imbalanced data: XGBoost with weighted and focal loss functions☆330Updated 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
- ☆15Updated 2 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
- Python code to prune ensembles☆13Updated 3 years ago
- Missing Data Imputation for Python☆247Updated last year
- 🛠️ Class-imbalanced Ensemble Learning Toolbox. | 类别不平衡/长尾机器学习库☆395Updated 5 months ago
- Feature Selection for Clustering☆96Updated 7 years ago
- An implementation of the focal loss to be used with LightGBM for binary and multi-class classification problems☆256Updated 5 years ago
- Active semi-supervised clustering algorithms for scikit-learn☆102Updated 5 years ago
- Ensemble learning related books, papers, videos, and toolboxes☆300Updated 6 years ago
- Feature Selection using Genetic Algorithm (DEAP Framework)☆371Updated 2 years ago
- Automating Outlier Detection via Meta-Learning (Code, API, and Contribution Instructions)☆186Updated 3 years ago
- ☆37Updated 5 years ago
- Python package for tackling multi-class imbalance problems. http://www.cs.put.poznan.pl/mlango/publications/multiimbalance/☆79Updated last year
- Code and documentation for experiments in the TreeExplainer paper☆188Updated 6 years ago
- Supplementary material for IJCNN paper "XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning"☆89Updated 6 years ago
- Our implementations of the Multi-class Imbalance learning algorithms (for the KBS paper)☆46Updated 6 years ago
- SMOGN: a Pre-processing Approach for Imbalanced Regression - LIDTA2017☆26Updated 8 years ago
- The code of the AAAI-19 paper "AFS: An Attention-based mechanism for Supervised Feature Selection".☆46Updated 6 years ago
- Code for the paper 'Variable Selection with Copula Entropy' published on Chinese Journal of Applied Probability and Statistics☆19Updated 3 years ago
- A Particle Swarm Optimization (PSO) for Feature Selection. Using PySwarm.☆53Updated 7 years ago
- ☆33Updated 8 months ago
- A python package for feature selection in python☆51Updated 4 years ago
- Can we predict accurately on the skewed data? What are the sampling techniques that can be used. Which models/techniques can be used in t…☆64Updated 5 years ago
- Feature selection in neural networks☆243Updated last year
- Play around with NGBoost and compare with LightGBM and XGBoost☆20Updated last year