Alternatives and similar repositories for gaussrank

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

• mxbi / ftim
  Feature-Time Instability Metric
  ☆44Updated 9 years ago
• zygmuntz / adversarial-validation
  Creating a better validation set when test examples differ from training examples
  ☆101Updated 9 years ago
• cgnorthcutt / rankpruning
  🧹 Formerly for binary classification with noisy labels. Replaced by cleanlab.
  ☆83Updated 3 years ago
• dkn22 / embedder
  Embed categorical variables via neural networks.
  ☆59Updated 2 years ago
• levyben / DeepSuperLearner
  DeepSuperLearner - Python implementation of the deep ensemble algorithm
  ☆135Updated 7 years ago
• cbonnett / MDN_Edward_Keras_TF
  ☆13Updated 9 years ago
• hamaadshah / gan_tensorflow
  Automatic feature engineering using Generative Adversarial Networks using TensorFlow.
  ☆51Updated 2 years ago
• johannespetrat / OptML
  Implementation of several black-box optimisation methods to tune hyperparameters of machine learning models.
  ☆78Updated 7 years ago
• ldv1 / LinXGBoost
  Extension of the awesome XGBoost to linear models at the leaves
  ☆82Updated 6 years ago
• goldentom42 / py_ml_utils
  Python utilities for Machine Learning competitions
  ☆32Updated 8 years ago
• mpearmain / gestalt
  A helper library for data science pipeline
  ☆36Updated 6 years ago
• NawfalTachfine / PredictionAPI
  Tutorial on deploying machine learning models to production
  ☆59Updated 5 years ago
• seba-1511 / randopt
  Streamlined machine learning experiment management.
  ☆107Updated 5 years ago
• caioaao / wolpert
  A stacked generalization framework. Built on top of scikit learn
  ☆57Updated 2 years ago
• arogozhnikov / infiniteboost
  InfiniteBoost: building infinite ensembles with gradient descent
  ☆183Updated 7 years ago
• yashu-seth / pytorch-tabular
  A python script for a PyTorch feed forward neural network for tabular data using categorical embeddings.
  ☆67Updated 6 years ago
• erlendd / covariate-shift-adaption
  An example of using a discriminator to correct for a difference in the distributions between the training and test data.
  ☆67Updated 8 years ago
• CyberZHG / keras-adabound
  AdaBound optimizer in Keras
  ☆56Updated 5 years ago
• MLWave / Black-Boxxy
  Some experiments into explaining complex black box ensemble predictions.
  ☆74Updated 5 years ago
• kiudee / cs-ranking
  Context-sensitive ranking and choice in Python with PyTorch
  ☆67Updated 2 years ago
• fukatani / stacked_generalization
  Library for machine learning stacking generalization.
  ☆117Updated 6 years ago
• MLWave / RGF-sklearn
  Scikit-learn API toy wrapper for Regularized Greedy Forests
  ☆44Updated 9 years ago
• maciejkula / binge
  Recommendation models that use binary rather than floating point operations at prediction time.
  ☆21Updated 8 years ago
• suriyadeepan / BayesianML
  Experiments in Bayesian Machine Learning
  ☆69Updated 6 years ago
• automl / pysmac
  simple python interface to SMAC.
  ☆21Updated 7 years ago
• spro / sconce-python
  ☆16Updated 8 years ago
• minerva-ml / steppy
  Lightweight, Python library for fast and reproducible experimentation
  ☆136Updated 6 years ago
• anonICLR2020 / node
  ☆26Updated 6 years ago
• szilard / benchm-dl
  Playing with various deep learning tools and network architectures
  ☆70Updated 7 years ago
• janvdvegt / KernelMixtureNetwork
  Kernel Mixture Network implementation with some minor tweaks
  ☆45Updated 8 years ago