Alternatives and similar repositories for mondrianforest

Users that are interested in mondrianforest are comparing it to the libraries listed below

• vitords / HoeffdingTree
  A Python implementation of the Hoeffding Tree algorithm.
  ☆48Updated 2 years ago
• bsharchilev / influence_boosting
  Supporting code for the paper "Finding Influential Training Samples for Gradient Boosted Decision Trees"
  ☆68Updated last year
• chaitanya-m / kdd2018
  Files submitted to kdd2018 for EFDT paper
  ☆22Updated 6 years ago
• YoungHJung / OnlineBoostingWithVFDT
  Online multiclass boosting algorithm that uses VFDT as weak learners
  ☆17Updated 6 years ago
• zalandoresearch / probrnn
  State space modeling with recurrent neural networks
  ☆45Updated 7 years ago
• Laurae2 / CategoricalAnalysis
  Analysis of Categorical Encodings for dense Decision Trees
  ☆41Updated 8 years ago
• lacava / few
  a feature engineering wrapper for sklearn
  ☆52Updated 5 years ago
• suriyadeepan / BayesianML
  Experiments in Bayesian Machine Learning
  ☆69Updated 6 years ago
• automl / pysmac
  simple python interface to SMAC.
  ☆21Updated 7 years ago
• udellgroup / oboe
  An AutoML pipeline selection system to quickly select a promising pipeline for a new dataset.
  ☆83Updated 3 years ago
• ldv1 / LinXGBoost
  Extension of the awesome XGBoost to linear models at the leaves
  ☆78Updated 6 years ago
• jeroenjanssens / scikit-sos
  A Python implementation of the Stochastic Outlier Selection algorithm
  ☆92Updated last year
• 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
• GuillaumeStaermanML / FIF
  Source code for the ACML 2019 paper "Functional Isolation Forest".
  ☆21Updated 3 years ago
• IntelLabs / TSAD-Evaluator
  Intel Labs open source repository for time series anomaly detection evaluator
  ☆42Updated 7 months ago
• franck-durand / tsboost
  Time Series Forecasting Framework
  ☆41Updated 2 years ago
• pcerda / string_categorical_encoders
  Scripts for paper "Encoding high-cardinality string categorical variables"
  ☆24Updated 5 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
• tmadl / sklearn-random-rotation-ensembles
  Scikit-learn compatible implementations of the Random Rotation Ensemble idea of (Blaser & Fryzlewicz, 2016)
  ☆43Updated 9 years ago
• wangtongada / BOA
  Bayesian or-of-and
  ☆35Updated 3 years ago
• johannespetrat / OptML
  Implementation of several black-box optimisation methods to tune hyperparameters of machine learning models.
  ☆77Updated 7 years ago
• albertcthomas / anomaly_tuning
  Learning hyperparameters for unsupervised anomaly detection
  ☆38Updated 5 years ago
• GaelVaroquaux / interpreting_ml_tuto
  Tutorial on interpreting and understanding machine learning models
  ☆69Updated 6 years ago
• jkfitzsimons / IPyNotebook_MachineLearning
  This contains a number of IP[y]: Notebooks that hopefully give a light to areas of bayesian machine learning.
  ☆34Updated 9 years ago
• BorgwardtLab / sampling-outlier-detection
  Rapid computation of distance-based outlierness scores via sampling
  ☆36Updated 9 years ago
• hamaadshah / gan_tensorflow
  Automatic feature engineering using Generative Adversarial Networks using TensorFlow.
  ☆51Updated 2 years ago
• jehangiramjad / tslib
  Time Series Forecasting and Imputation
  ☆48Updated 3 years ago
• alteryx / DL-DB
  Deep learning for time-varying multi-entity datasets
  ☆17Updated 7 years ago
• statefb / singular-spectrum-transformation
  fast implementation of singular spectrum transformation (change point detection algorithm)
  ☆51Updated 7 years ago
• iskandr / knnimpute
  Python implementations of kNN imputation
  ☆31Updated 8 years ago