Alternatives and similar repositories for bank-account-fraud:

Users that are interested in bank-account-fraud are comparing it to the libraries listed below

• NextBrain-ai / nbsynthetic
  nbsynthetic is simple and robust tabular synthetic data generation library for small and medium size datasets
  ☆65Updated 2 years ago
• amazon-science / fraud-dataset-benchmark
  Repository for Fraud Dataset Benchmark
  ☆165Updated last year
• kathrinse / be_great
  A novel approach for synthesizing tabular data using pretrained large language models
  ☆304Updated 5 months ago
• feedzai / fairgbm
  Train Gradient Boosting models that are both high-performance *and* Fair!
  ☆103Updated 9 months ago
• LevinRoman / tabular-transfer-learning
  A repo for transfer learning with deep tabular models
  ☆102Updated 2 years ago
• puhsu / tabular-dl-pretrain-objectives
  Revisiting Pretrarining Objectives for Tabular Deep Learning
  ☆63Updated 2 years ago
• IFCA-Advanced-Computing / frouros
  Frouros: an open-source Python library for drift detection in machine learning systems.
  ☆212Updated 2 months ago
• Baukebrenninkmeijer / table-evaluator
  Evaluate real and synthetic datasets against each other
  ☆86Updated 2 months ago
• ykwon0407 / WeightedSHAP
  WeightedSHAP: analyzing and improving Shapley based feature attributions (NeurIPS 2022)
  ☆160Updated 2 years ago
• Team-TUD / CTAB-GAN
  Official git for "CTAB-GAN: Effective Table Data Synthesizing"
  ☆83Updated last year
• kathrinse / TabSurvey
  Experiments on Tabular Data Models
  ☆276Updated last year
• linkedin / TE2Rules
  Python library to explain Tree Ensemble models (TE) like XGBoost, using a rule list.
  ☆51Updated 11 months ago
• navefr / ExKMC
  Expanding Explainable K-Means Clustering
  ☆95Updated 2 years ago
• felipemaiapolo / detectshift
  Dataset shift diagnostics in Python
  ☆34Updated last year
• Team-TUD / CTAB-GAN-Plus
  Official GitHub for CTAB-GAN+
  ☆74Updated 10 months ago
• salimamoukou / acv00
  ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any…
  ☆100Updated 2 years ago
• interpretml / TalkToEBM
  A Natural Language Interface to Explainable Boosting Machines
  ☆65Updated 8 months ago
• nathanwang000 / Shapley-Flow
  ☆50Updated last year
• givasile / effector
  Effector - a Python package for global and regional effect methods
  ☆74Updated this week
• worldbank / REaLTabFormer
  A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.
  ☆223Updated 2 weeks ago
• feedzai / timeshap
  TimeSHAP explains Recurrent Neural Network predictions.
  ☆171Updated last year
• interpretml / gam-changer
  Editing machine learning models to reflect human knowledge and values
  ☆124Updated last year
• steverab / failing-loudly
  Code repository for our paper "Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift": https://arxiv.org/abs/1810.119…
  ☆103Updated last year
• Moffran / calibrated_explanations
  Repository for the explanation method Calibrated Explanations (CE)
  ☆64Updated 3 weeks ago
• AstraZeneca / SubTab
  The official implementation of the paper, "SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning"
  ☆144Updated 2 years ago
• sdv-dev / SDMetrics
  Metrics to evaluate quality and efficacy of synthetic datasets.
  ☆228Updated this week
• valeman / Multi-class-probabilistic-classification
  Multi-class probabilistic classification using inductive and cross Venn–Abers predictors
  ☆44Updated 2 years ago
• scikit-learn-contrib / hiclass
  A python library for hierarchical classification compatible with scikit-learn
  ☆122Updated 3 weeks ago
• pbiecek / xai_stories
  XAI Stories. Case studies for eXplainable Artificial Intelligence
  ☆29Updated 4 years ago
• ptocca / VennABERS
  Fast implementation of Venn-ABERS probabilistic predictors
  ☆72Updated last year