• MALLET

  • Referenced in 23 articles [sw10602]
  • topic modeling, information extraction, and other machine learning applications to text. MALLET includes sophisticated tools ... evaluating classifier performance using several commonly used metrics. In addition to classification, MALLET includes tools...
  • MOE

  • Referenced in 3 articles [sw36871]
  • metric optimization engine; a new open source, machine learning service for optimal experiment design...
  • BENEDICT

  • Referenced in 13 articles [sw35868]
  • hybrid methodology for learning belief networks: BENEDICT. Previous algorithms for the construction of belief networks ... either on independence criteria or on scoring metrics. The aim of this paper...
  • DeepSORT

  • Referenced in 2 articles [sw39576]
  • Realtime Tracking with a Deep Association Metric. Simple Online and Realtime Tracking (SORT ... training stage where we learn a deep association metric on a large-scale person...
  • AIF360

  • Referenced in 6 articles [sw33037]
  • machine learning models throughout the AI application lifecycle. Containing over 70 fairness metrics...
  • River

  • Referenced in 1 article [sw39427]
  • state-of-the-art learning methods, data generators/transformers, performance metrics and evaluators for different stream...
  • Cardinal

  • Referenced in 1 article [sw42233]
  • Cardinal, a metric-based Active learning framework. In Active learning, a trained model is used ... shot experiment is hard, but metrics have been proven to help by detecting strategies performing...
  • DOTmark

  • Referenced in 7 articles [sw17085]
  • metric or earth mover’s distance (EMD) is a useful tool in statistics, machine learning...
  • TensorBoard

  • Referenced in 2 articles [sw30736]
  • tooling needed for machine learning experimentation:Tracking and visualizing metrics such as loss and accuracy...
  • MEKA

  • Referenced in 12 articles [sw15429]
  • variety of methods for this type of learning. We present MEKA: an open-source Java ... wealth of multi-label classifiers, evaluation metrics, and tools for multi-label experiments and development...
  • GlobalMIT

  • Referenced in 3 articles [sw38463]
  • This article presents GlobalMIT, a toolbox for learning the globally optimal DBN structure from gene ... scoring metric named mutual information test (MIT). With MIT, the task of learning the globally...
  • CARLA

  • Referenced in 7 articles [sw35046]
  • model trained via reinforcement learning. The approaches are evaluated in controlled scenarios of increasing difficulty ... their performance is examined via metrics provided by CARLA, illustrating the platform’s utility...
  • MWMOTE

  • Referenced in 14 articles [sw32596]
  • problems. MWMOTE first identifies the hard-to-learn informative minority class samples and assigns them ... existing methods in terms of various assessment metrics, such as geometric mean (G-mean...
  • FEQA

  • Referenced in 1 article [sw42113]
  • embedding similarity, and learned language understanding models, our QA-based metric has significantly higher correlation...
  • Latte

  • Referenced in 1 article [sw40922]
  • easily extended to support other deep learning frameworks. Using NumPy-based and framework-agnostic implementation ... reproducible, consistent, and deterministic metric calculations regardless of the deep learning framework of choice...
  • iLoc-Animal

  • Referenced in 20 articles [sw22427]
  • depth studies. By introducing the ”multi-label learning” approach, a new predictor, called iLoc-Animal ... multi-label approach and the rigorous measurement metrics can also be used to investigate many...
  • NeuroSim+

  • Referenced in 1 article [sw38117]
  • system-level learning accuracy and hardware performance metrics. It has a hierarchical organization from ... analog eNVM based array architectures for online learning and offline classification. The source code...
  • PNKH-B

  • Referenced in 2 articles [sw40451]
  • case in large-scale parameter estimation, machine learning, and image processing. In each iteration, PNKH ... determine the search direction and construct the metric used in a projected line search ... PNKH-B similar to a projected variable metric method. We present an interior point method ... learning, and image reconstruction, we show that the consistent use of the Hessian metric...
  • GEMLeR

  • Referenced in 2 articles [sw12033]
  • machine learning algorithms. They can be used for estimation of different quality metrics (e.g. accuracy ... inspired by an increasing need in machine learning / bioinformatics communities for a collection of microarray...
  • Comet.ml

  • Referenced in 1 article [sw27031]
  • hyper parameters, metrics, code, stdout tracking. Supports Keras, Tensorflow, PyTorch, scikit-learn...