bsharchilev / influence_boosting
Supporting code for the paper "Finding Influential Training Samples for Gradient Boosted Decision Trees"
☆67Updated 7 months ago
Alternatives and similar repositories for influence_boosting:
Users that are interested in influence_boosting are comparing it to the libraries listed below
- Data and code related to the paper "Probabilistic matrix factorization for automated machine learning", NIPS, 2018.☆40Updated 3 years ago
- An example of using a discriminator to correct for a difference in the distributions between the training and test data.☆67Updated 8 years ago
- ☆74Updated 6 years ago
- An AutoML pipeline selection system to quickly select a promising pipeline for a new dataset.☆82Updated 3 years ago
- This is the official clone for the implementation of the NIPS18 paper Multi-Layered Gradient Boosting Decision Trees (mGBDT) .☆102Updated 6 years ago
- Discretization with Fayyad and Irani's minimum description length principle criterion (MDLPC)☆60Updated 6 years ago
- Reliability diagrams, Platt's scaling, isotonic regression☆75Updated 10 years ago
- State space modeling with recurrent neural networks☆43Updated 6 years ago
- A density ratio estimator package for python using the KLIEP algorithm.☆106Updated 4 years ago
- Public solution for AutoSeries competition☆72Updated 5 years ago
- Development Repository for GPU-accelerated GBDT training☆60Updated 7 years ago
- ☆39Updated 12 years ago
- A Performance Benchmark of Different AutoML Frameworks☆35Updated last year
- (ICML2020) “Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models’’☆31Updated last year
- Deep Neural Decision Trees☆161Updated 2 years ago
- ☆124Updated 3 years ago
- Multiple imputation utilising denoising autoencoder for approximate Bayesian inference☆119Updated 4 years ago
- ☆69Updated 4 years ago
- Library for machine learning stacking generalization.☆117Updated 5 years ago
- An implementation of the Deep Neural Decision Forests in PyTorch☆156Updated 5 years ago
- AutoGBT is used for AutoML in a lifelong machine learning setting to classify large volume high cardinality data streams under concept-dr…☆114Updated 5 years ago
- Tensorflow implementation of a Tree☆36Updated 5 years ago
- Extension of the awesome XGBoost to linear models at the leaves☆78Updated 5 years ago
- Preparing continuous features for neural networks with GaussRank☆45Updated 6 years ago
- ☆71Updated 4 years ago
- ☆26Updated 5 years ago
- Context-sensitive ranking and choice in Python with PyTorch☆66Updated last year
- Python implementation of stacked generalization classifier. Plays nice with sklearn.