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☆262Updated last year
- XGBoost for label-imbalanced data: XGBoost with weighted and focal loss functions☆333Updated 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☆111Updated last year
- A missing value imputation library based on machine learning. It's implementation missForest, simple edition of MICE(R pacakge), knn, EM,…☆107Updated last year
- Cost-Sensitive Learning / ReSampling / Weighting / Thresholding / BorderlineSMOTE / AdaCost / etc.☆110Updated 5 years ago
- The code of the AAAI-19 paper "AFS: An Attention-based mechanism for Supervised Feature Selection".☆47Updated 6 years ago
- Our implementations of the Multi-class Imbalance learning algorithms (for the KBS paper)☆46Updated 6 years ago
- Oversampling for imbalanced learning based on k-means and SMOTE☆129Updated 4 years ago
- 🛠️ Class-imbalanced Ensemble Learning Toolbox. | 类别不平衡/长尾机器学习库☆408Updated 7 months ago
- ☆37Updated 5 years ago
- Python package for tackling multi-class imbalance problems. http://www.cs.put.poznan.pl/mlango/publications/multiimbalance/☆78Updated last year
- Automating Outlier Detection via Meta-Learning (Code, API, and Contribution Instructions)☆186Updated 3 years ago
- Code and documentation for experiments in the TreeExplainer paper☆189Updated 6 years ago
- Feature selection in neural networks☆248Updated last year
- 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 6 years ago
- Fast Correlation-Based Feature Selection☆31Updated 8 years ago
- ☆15Updated 2 years ago
- Python3 binding to mRMR Feature Selection algorithm (currently not maintained)☆141Updated last year
- (Python, R) Cost-sensitive multiclass classification (Weighted-All-Pairs, Filter-Tree & others)☆49Updated 7 months ago
- This project is a research on how to extract rules from the existing data using trained Decision Tree. The dataset used to train the mode…☆16Updated 6 years ago
- Missing Data Imputation for Python☆248Updated last year
- AutoLearn, a domain independent regression-based feature learning algorithm.☆30Updated 6 years ago
- Ensemble learning related books, papers, videos, and toolboxes☆302Updated 6 years ago
- Supplementary material for IJCNN paper "XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning"☆89Updated 6 years ago
- The stream-learn is an open-source Python library for difficult data stream analysis.☆66Updated 3 months ago
- Active semi-supervised clustering algorithms for scikit-learn☆103Updated 5 years ago
- Tutorial on cost-sensitive boosting and calibrated AdaMEC.☆26Updated 8 years ago
- ☆170Updated 5 years ago
- Feature selection for deep learning models.☆13Updated 4 years ago