optuna / optuna-examplesLinks
Examples for https://github.com/optuna/optuna
☆818Updated this week
Alternatives and similar repositories for optuna-examples
Users that are interested in optuna-examples are comparing it to the libraries listed below
Sorting:
- Real-time Web Dashboard for Optuna.☆724Updated last week
- A standard framework for modelling Deep Learning Models for tabular data☆1,615Updated last month
- Implementation of TabTransformer, attention network for tabular data, in Pytorch☆1,048Updated last week
- Research on Tabular Deep Learning: Papers & Packages☆1,088Updated last year
- XGBoost + Optuna☆725Updated last year
- mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.☆618Updated last year
- ☆500Updated last year
- Synthetic Minority Over-Sampling Technique for Regression☆348Updated last year
- PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf☆2,888Updated last year
- (ICLR 2025) TabM: Advancing Tabular Deep Learning With Parameter-Efficient Ensembling☆917Updated last month
- A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.☆583Updated last year
- ML models + benchmark for tabular data classification and regression☆313Updated last week
- (NeurIPS 2021) Revisiting Deep Learning Models for Tabular Data☆310Updated last year
- A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.☆641Updated last year
- Extended functionalities for Optuna in combination with third-party libraries.☆62Updated last week
- Natural Gradient Boosting for Probabilistic Prediction☆1,818Updated last month
- Multiple Imputation with LightGBM in Python☆402Updated 2 months ago
- Linear Prediction Model with Automated Feature Engineering and Selection Capabilities☆535Updated last week
- Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshad…☆674Updated 10 months ago
- An extension of LightGBM to probabilistic modelling☆350Updated 2 weeks ago
- A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.☆469Updated 2 years ago
- The official PyTorch implementation of recent paper - SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive …☆460Updated 4 years ago
- ☆206Updated 4 years ago
- Experiments on Tabular Data Models☆281Updated 2 years ago
- (NeurIPS 2022) On Embeddings for Numerical Features in Tabular Deep Learning☆393Updated 8 months ago
- Flexible time series feature extraction & processing☆437Updated last year
- An extension of XGBoost to probabilistic modelling☆679Updated 2 weeks ago
- Feature engineering package with sklearn like functionality☆2,173Updated last month
- A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.☆1,500Updated this week
- An intuitive library to extract features from time series.☆1,067Updated 4 months ago