• SimpleMKL

  • Referenced in 69 articles [sw12290]
  • SimpleMKL can be applied beyond binary classification, for problems like regression, clustering (one-class classification...
  • XNOR-Net

  • Referenced in 21 articles [sw39593]
  • XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks. We propose two efficient approximations ... rather than GPUs) in real-time. Our binary networks are simple, accurate, efficient, and work ... ImageNet classification task. The classification accuracy with a Binary-Weight-Network version of AlexNet...
  • ENDER

  • Referenced in 15 articles [sw12831]
  • algorithm is tailored for regression and binary classification problems. It uses the boosting approach...
  • DiSCO

  • Referenced in 12 articles [sw28439]
  • distributed ridge regression, logistic regression and binary classification with a smoothed hinge loss...
  • Fast-dm

  • Referenced in 11 articles [sw09136]
  • empirical response time distributions of any binary classification task. Fast-dm is easy...
  • IMDB

  • Referenced in 16 articles [sw36449]
  • Dataset. This is a dataset for binary sentiment classification containing substantially more data than previous...
  • Split Step Explorer

  • Referenced in 15 articles [sw24413]
  • eigenvalues are allowed. The phase classification by integer or binary indices extends the classification known...
  • SIRENE

  • Referenced in 7 articles [sw17419]
  • into a large number of local binary classification problems, that focus on separating target genes...
  • ATPboost

  • Referenced in 4 articles [sw28626]
  • setting, the learning is implemented as binary classification that estimates the pairwise-relevance of (theorem ... XGBoost gradient boosting algorithm. Learning in the binary setting however requires negative examples, which...
  • ROSE

  • Referenced in 4 articles [sw25503]
  • package provides functions to deal with binary classification problems in the presence of imbalanced classes...
  • NSVMOOP

  • Referenced in 4 articles [sw14484]
  • optimization problem (NSVMOOP) for binary classification. Our NSVMOOP is formulated aiming to separate classes from...
  • WilcoxCV

  • Referenced in 3 articles [sw08147]
  • settings, for use in microarray-based binary classification...
  • rotationForest

  • Referenced in 3 articles [sw24760]
  • /TPAMI.2006.211>”) for binary classification. Rotation forest is an ensemble method where each base classifier (tree...
  • IRIC

  • Referenced in 2 articles [sw32593]
  • IRIC: An R library for binary imbalanced classification. Imbalanced classification is a challenging issue ... wide set of solutions for imbalanced binary classification. IRIC not only provides a new implementation...
  • GaussianProcesses.jl

  • Referenced in 2 articles [sw42274]
  • handle non-Gaussian data (e.g., binary classification models) and sparse approximations for scalable Gaussian processes...
  • cutpointr

  • Referenced in 1 article [sw40263]
  • Determine and Evaluate Optimal Cutpoints in Binary Classification Tasks. Estimate cutpoints that optimize a specified ... metric in binary classification tasks and validate performance using bootstrapping. Some methods for more robust...
  • GAMens

  • Referenced in 1 article [sw32661]
  • GAMrsm and GAMens Ensemble Classifiers for Binary Classification. Implements the GAMbag, GAMrsm and GAMens ensemble ... classifiers for binary classification (De Bock et al., 2010) . The ensembles implement...
  • InformationValue

  • Referenced in 1 article [sw33586]
  • Performance Analysis and Companion Functions for Binary Classification Models. Provides companion function for analysing ... performance of classification models. Also, provides function to optimise probability cut- off score based ... accuracy improvement in binary classification models...
  • nproc

  • Referenced in 1 article [sw36077]
  • Characteristic (NP-ROC) Curves. In many binary classification applications, such as disease diagnosis and spam...
  • CoMIK

  • Referenced in 1 article [sw35270]
  • identifies not just the features useful towards classification but also their locations in the variable ... evidenced by the results of three binary classification experiments, aided by recently introduced visualization techniques...