UdayLab / PAMI
PAMI is a Python library containing 100+ algorithms to discover useful patterns in various databases across multiple computing platforms. (Active)
β258Updated last week
Alternatives and similar repositories for PAMI:
Users that are interested in PAMI are comparing it to the libraries listed below
- scikit-mine : pattern mining in Pythonβ73Updated last year
- [AAAI 2022] Seq2Pat: Sequence-to-Pattern Generation Libraryβ132Updated 3 months ago
- Python SPMF Wrapper π πβ66Updated 10 months ago
- Exceptional Model Mining is a descriptive data mining technique to find interesting patterns in datasets. This package contains a Python β¦β11Updated 9 months ago
- C# code of ECSM (AI 2016 conference)β11Updated 8 years ago
- [AMAI 2024] Selective: Feature Selection Libraryβ68Updated 3 months ago
- A visualization tool that supports queries and pattern mining for event sequence explorationβ31Updated 3 years ago
- LoCoMotif is a time series motif discovery method that discovers variable-length motif sets in multivariate time series using time warpinβ¦β22Updated last month
- A power-full Shapley feature selection method.β203Updated 10 months ago
- The stream-learn is an open-source Python library for difficult data stream analysis.β63Updated 2 weeks ago
- [AAAI 2021] TextWiser: Text Featurization Libraryβ56Updated last week
- Random Forest or XGBoost? It is Time to Explore LCEβ66Updated last year
- Scikit-Learn compatible transformer that turns categorical variables into dense entity embeddings.β42Updated last year
- NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for β¦β106Updated 2 years ago
- Custom Loss Functions and Evaluation Metrics for XGBoost and LightGBMβ36Updated 3 years ago
- Describe data in terms of informative and concise sets of patternsβ11Updated 3 years ago
- Python library to explain Tree Ensemble models (TE) like XGBoost, using a rule list.β52Updated 11 months ago
- A python library to build Model Trees with Linear Models at the leaves.β373Updated 8 months ago
- All Relevant Feature Selectionβ131Updated last month
- Synthetic Data Generation for mixed-type, multivariate time series.β111Updated 3 weeks ago
- An unsupervised feature selection technique using supervised algorithms such as XGBoostβ89Updated last year
- Example usage of scikit-htsβ57Updated 2 years ago
- Automatically transform all categorical, date-time, NLP variables to numeric in a single line of code for any data set any size.β64Updated 2 months ago
- Hierarchical Time Series Forecasting with a familiar APIβ224Updated last year
- hgboost is a python package for hyper-parameter optimization for xgboost, catboost or lightboost using cross-validation, and evaluating tβ¦β64Updated 3 weeks ago
- AutoML for clustering models in sklearn.β61Updated 2 years ago
- xverse (XuniVerse) is collection of transformers for feature engineering and feature selectionβ117Updated last year
- An automated machine learning tool aimed to facilitate AutoML research.β96Updated 6 months ago
- ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for anyβ¦β100Updated 2 years ago
- Quick and Easy Time Series Outlier Detectionβ108Updated 8 months ago