• Scikit

  • Referenced in 452 articles [sw08058]
  • machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing...
  • Neural Network Toolbox

  • Referenced in 175 articles [sw07378]
  • form equation. Neural Network Toolbox supports supervised learning with feedforward, radial basis, and dynamic networks...
  • RCV1

  • Referenced in 117 articles [sw07279]
  • benchmark several widely used supervised learning methods on RCV1-v2, illustrating the collection’s properties...
  • SimpleMKL

  • Referenced in 65 articles [sw12290]
  • kernel and the associated predictor in supervised learning settings. For the support vector machine...
  • LabelMe

  • Referenced in 44 articles [sw36633]
  • research. Such data is useful for supervised learning and quantitative evaluation. To achieve this ... number of labels using minimal user supervision and images from...
  • SVMstruct

  • Referenced in 30 articles [sw04075]
  • multivariate or structured outputs. It performs supervised learning by approximating a mapping...
  • MLC++

  • Referenced in 41 articles [sw13539]
  • machine learning library in C++. We present MLC++, a library ... classes and tools for supervised machine learning. While MLC++ provides general learning algorithms that...
  • auto-sklearn

  • Referenced in 21 articles [sw33039]
  • sklearn provides out-of-the-box supervised machine learning. Built around the scikit-learn machine...
  • DiSCO

  • Referenced in 11 articles [sw28439]
  • algorithm for empirical risk minimization in machine learning. The algorithm is based on an inexact ... loss. In a standard setting for supervised learning, where the n data points are i.i.d...
  • ddalpha

  • Referenced in 11 articles [sw16053]
  • ddalpha. Contains procedures for depth-based supervised learning, which are entirely non-parametric, in particular...
  • MBT

  • Referenced in 6 articles [sw08004]
  • based learning is a form of supervised learning based on similarity-based reasoning. The part ... most similar cases held in memory. Supervised learning approaches are useful when a tagged corpus...
  • LWPR

  • Referenced in 7 articles [sw13543]
  • locally weighted projection regression (LWPR), a supervised learning algorithm that is capable of handling high...
  • STL-10 dataset

  • Referenced in 22 articles [sw39164]
  • examples is provided to learn image models prior to supervised training. The primary challenge ... challenging benchmark for developing more scalable unsupervised learning methods. Reference: Adam Coates, Honglak Lee, Andrew...
  • Statistics Toolbox

  • Referenced in 18 articles [sw10157]
  • Statistics Toolbox™ provides statistical and machine learning algorithms and tools for organizing, analyzing, and modeling ... squares regression. The toolbox provides supervised and unsupervised machine learning algorithms, including support vector machines...
  • Learn++

  • Referenced in 8 articles [sw37991]
  • Learn++: an incremental learning algorithm for supervised neural networks. We introduce Learn++, an algorithm ... pattern classifiers. The proposed algorithm enables supervised NN paradigms, such as the multilayer perceptron ... previously used data during subsequent incremental learning sessions, yet at the same time, it does...
  • Horizon

  • Referenced in 5 articles [sw31157]
  • with Horizon significantly outperformed and replaced supervised learning systems at Facebook...
  • SOFAR

  • Referenced in 5 articles [sw31665]
  • broad applications to both unsupervised and supervised learning tasks, such as biclustering with sparse singular...
  • Spider

  • Referenced in 8 articles [sw10713]
  • spider - machine learning toolbox for Matlab. It’s a library of objects in Matlab ... reasonably) large unsupervised, supervised or semi-supervised machine learning problems. Aims to become a complete...
  • graph2vec

  • Referenced in 8 articles [sw32340]
  • neural embedding framework named graph2vec to learn data-driven distributed representations of arbitrary sized graphs ... graph classification, clustering and even seeding supervised representation learning approaches. Our experiments on several benchmark...