Alternatives and similar repositories for openml-pimp

Users that are interested in openml-pimp are comparing it to the libraries listed below

• itsrainingdata / sparsebn
  Software for learning sparse Bayesian networks
  ☆43Updated 4 years ago
• openml / Study-14
  ☆13Updated 3 years ago
• ja-thomas / OMLbots
  ☆13Updated 7 years ago
• markm541374 / gpbo
  gpbo
  ☆25Updated 4 years ago
• arapat / sparrow
  Sparrow is a boosting algorithm implementation that is optimized for training on very large datasets and/or in the limited memory setting…
  ☆21Updated 4 years ago
• pymc-learn / pymc-learn-book
  Book: Practical Probabilistic Machine Learning in Python
  ☆10Updated 4 years ago
• lrouviere / AGB
  These are the codes used in the paper "Accelerated Gradient Boosting" by G. Biau, B. Cadre, and L. Rouvière.
  ☆17Updated 7 years ago
• abhishekmalali / h2o-hyperopt
  Library for integrated use of H2O with Hyperopt
  ☆13Updated last year
• MI2DataLab / pyBreakDown
  Python implementation of R package breakDown
  ☆43Updated 2 years ago
• BigBayes / SGRLD
  Stochastic Gradient Riemannian Langevin Dynamics
  ☆33Updated 10 years ago
• davpinto / fastknn
  Fast k-Nearest Neighbors Classifier for Large Datasets
  ☆69Updated 7 years ago
• ebonilla / AutoGP
  Code for AutoGP
  ☆27Updated 5 years ago
• lendle / SuPyLearner
  An implementation of the SuperLearner algorithm in Python based on scikit-learn.
  ☆25Updated 11 years ago
• ptoulis / implicit-sgd
  Using stochastic gradient descent (SGD) with explicit and implicit updates to fit large-scale statistical models.
  ☆16Updated 10 years ago
• isidroc / conformal
  Conformal prediction in R
  ☆32Updated 5 years ago
• tansey / functionalmf
  Functional matrix factorization via Bayesian tensor filtering
  ☆13Updated 2 years ago
• NICTA / revrand
  A library of scalable Bayesian generalised linear models with fancy features
  ☆60Updated 7 years ago
• PhilippPro / tunability
  ☆8Updated 6 years ago
• automl / HPOlib1.5
  ☆69Updated 4 years ago
• slds-lmu / paper_2019_iml_measures
  Quantifying Interpretability of Arbitrary Machine Learning Models Through Functional Decomposition
  ☆16Updated 5 years ago
• szilard / awesome-GBMs
  A curated list of gradient boosting machines (GBM) resources
  ☆10Updated 6 years ago
• Laurae2 / CategoricalAnalysis
  Analysis of Categorical Encodings for dense Decision Trees
  ☆41Updated 8 years ago
• ajverster / RotationForest
  An implementation of the Rotation Forest algorithm from Rodriguez et al. 2006
  ☆18Updated 12 years ago
• SelfExplainML / GamiNet
  GAMI-Net: Generalized Additive Models with Structured Interactions
  ☆31Updated 3 years ago
• ecpolley / SuperLearnerExtra
  Additional functions for the SuperLearner R package. A collection of mostly wrapper functions that might be useful for the SuperLearner b…
  ☆20Updated last year
• joelgrus / odscnet
  repo for my ODSC West 2017 Talk: "Livecoding Madness: Let's Build a Deep Learning Library"
  ☆13Updated 7 years ago
• operalib / operalib
  Learning with operator-valued kernels
  ☆22Updated 2 years ago
• paobranco / UBL
  An R package for utility-based learning
  ☆34Updated 7 months ago
• GuillaumeStaermanML / FIF
  Source code for the ACML 2019 paper "Functional Isolation Forest".
  ☆21Updated 3 years ago
• balajiln / pgbart
  Particle Gibbs for Bayesian Additive Regression Trees
  ☆32Updated 10 years ago