• node2vec

  • Referenced in 28 articles [sw27202]
  • state-of-the-art techniques on multi-label classification and link prediction in several real...
  • ML-KNN

  • Referenced in 58 articles [sw12923]
  • world multi-label learning problems, i.e. Yeast gene functional analysis, natural scene classification and automatic ... superior performance to some well-established multi-label learning algorithms...
  • MULAN

  • Referenced in 58 articles [sw08062]
  • learning from multi-label data. It offers a variety of classification, ranking, thresholding and dimensionality...
  • MEKA

  • Referenced in 12 articles [sw15429]
  • multi-label/multi-target extension to WEKA. Multi-label classification has rapidly attracted interest ... practical application, and a wealth of multi-label classifiers, evaluation metrics, and tools for multi...
  • MLTSVM

  • Referenced in 8 articles [sw27170]
  • twin support vector machine (MLTSVM) for multi-label classification. MLTSVM determines multiple nonparallel hyperplanes ... twin support vector machine (TWSVM) for multi-label classification. To speed up the training procedure ... both synthetic and real-world multi-label datasets confirm the feasibility and effectiveness...
  • CNN-RNN

  • Referenced in 6 articles [sw28401]
  • Unified Framework for Multi-label Image Classification. While deep convolutional neural networks (CNNs) have shown ... image. Traditional approaches to multi-label image classification learn independent classifiers for each category ... label embedding to characterize the semantic label dependency as well as the image-label relevance ... than the state-of-the-art multi-label classification model...
  • iATC-mHyb

  • Referenced in 21 articles [sw24529]
  • iATC-mHyb: a hybrid multi-label classifier for predicting the classification of anatomical therapeutic chemicals...
  • AnnexML

  • Referenced in 3 articles [sw30153]
  • Approximate Nearest Neighbor Search for Extreme Multi-label Classification. Extreme multi-label classification methods have...
  • scikit-multilearn

  • Referenced in 3 articles [sw18802]
  • scikit-based Python environment for performing multi-label classification. Scikit-multilearn is a Python library ... performing multi-label classification. The library is compatible with the scikit/scipy ecosystem and uses sparse ... provides native Python implementations of popular multi-label classification methods alongside novel framework for label...
  • DiSMEC

  • Referenced in 2 articles [sw30154]
  • DiSMEC - Distributed Sparse Machines for Extreme Multi-label Classification. Extreme multi-label classification refers ... supervised multi-label learning involving hundreds of thousands or even millions of labels. Datasets ... extreme classification exhibit fit to power-law distribution, i.e. a large fraction of labels have ... approaches for extreme multi-label classification attempt to capture correlation among labels by embedding...
  • LibD3C

  • Referenced in 4 articles [sw21627]
  • through employing a problem transformation for multi-label classification. Empirical study shows that D3C exhibits ... high-performance methods, and experiments in multi-label datasets verify the feasibility of multi-label...
  • LNEMLC

  • Referenced in 1 article [sw28400]
  • LNEMLC: Label Network Embeddings for Multi-Label Classification. Multi-label classification aims to classify instances ... exclusive labels. Most approaches on multi-label classification focus on effective adaptation or transformation ... propose a new multi-label classification scheme, LNEMLC - Label Network Embedding for Multi-Label Classification ... learning and inference of any base multi-label classifier. The approach allows capturing of labels...
  • MLC Toolbox

  • Referenced in 1 article [sw28399]
  • Toolbox: A MATLAB/OCTAVE Library for Multi-Label Classification. Multi-Label Classification toolbox is a MATLAB/OCTAVE ... library for Multi-Label Classification (MLC). There exists a few Java libraries...
  • HCP

  • Referenced in 2 articles [sw28402]
  • Flexible CNN Framework for Multi-Label Image Classification. Convolutional Neural Network (CNN) has demonstrated promising ... label image classification tasks. However, how CNN best copes with multi-label images still remains...
  • utiml

  • Referenced in 3 articles [sw27783]
  • Learning. Multi-label learning strategies and others procedures to support multi- label classification...
  • rFerns

  • Referenced in 1 article [sw24307]
  • /TPAMI.2009.23>, modified for generic and multi-label classification and featuring OOB error approximation and importance...
  • ATPboost

  • Referenced in 2 articles [sw28626]
  • that use multi-label setting, the learning is implemented as binary classification that estimates ... show significant improvement over the multi-label approach...
  • TreeBoost.MH

  • Referenced in 2 articles [sw20539]
  • propose TreeBoost.MH, an algorithm for multi-label Hierarchical Text Categorization (HTC) consisting of a hierarchical ... paying attention to the topology of the classification scheme. It also embodies the novel intuition...
  • MLPUGS

  • Referenced in 0 articles [sw15744]
  • classifier chains (CC’s) for multi-label prediction. Users can employ an external package ... multi-core environment. New observations are classified using a Gibbs sampler since each unobserved label ... models to produce binary or probabilistic classifications...
  • mLASSO-Hum

  • Referenced in 1 article [sw16468]
  • problems, this paper proposes an interpretable multi-label predictor, namely mLASSO-Hum, which can yield ... also play important roles in the final classification decisions. For readers’ convenience, the mLASSO...