• TPOT

  • Referenced in 11 articles [sw18808]
  • Tree-based Pipeline Optimization Tool for Automating Machine Learning. As data science becomes more mainstream ... scalable. In response to this demand, automated machine learning (AutoML) researchers have begun building systems ... that automate the process of designing and optimizing machine learning pipelines. In this paper...
  • MaLARea

  • Referenced in 50 articles [sw10278]
  • Automated Reasoning tools (now the E and the SPASS ATP systems) with a machine learning...
  • ML-plan

  • Referenced in 4 articles [sw40694]
  • plan: automated machine learning via hierarchical planning. Automated machine learning (AutoML) seeks to automatically select...
  • OBOE

  • Referenced in 3 articles [sw35832]
  • most challenging tasks in machine learning. Automated machine learning (AutoML) seeks to automate these tasks...
  • GNMT

  • Referenced in 28 articles [sw26579]
  • Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, with ... work, we present GNMT, Google’s Neural Machine Translation system, which attempts to address many...
  • PyODDS

  • Referenced in 3 articles [sw38163]
  • Outlier Detection System with Automated Machine Learning. Outlier detection is an important task for various ... fill this gap, we present PyODDS, an automated end-to-end Python system for Outlier ... with or without data science or machine learning background. In particular, we demonstrate PyODDS...
  • DriveML

  • Referenced in 1 article [sw32864]
  • recent years, the concept of automated machine learning has become very popular. Automated Machine Learning ... package i.e. DriveML for automated machine learning. DriveML helps in implementing some of the pillars ... automated machine learning pipeline such as automated data preparation, feature engineering, model building and model ... developer’s errors, optimal tuning of machine learning models and reproducibility...
  • AutoGL

  • Referenced in 1 article [sw38082]
  • applications of machine learning on graphs. Automated machine learning (AutoML) on graphs ... horizon to automatically design the optimal machine learning algorithm for a given graph task. However ... Learning (AutoGL), the first library for automated machine learning on graphs. AutoGL is open-source ... extended. Specifically, We propose an automated machine learning pipeline for graph data containing four modules...
  • autoBagging

  • Referenced in 2 articles [sw21034]
  • Workflows with Metalearning. A framework for automated machine learning. Concretely, the focus...
  • AutoNE

  • Referenced in 2 articles [sw38085]
  • serves as the bridge between machine learning and network data. Despite their widespread success ... order to achieve satisfactory performance. Though automated machine learning (AutoML) has achieved promising results when...
  • MLaut

  • Referenced in 1 article [sw27171]
  • Machine Learning Automation Toolbox (MLaut). In this paper we present MLaut (Machine Learning AUtomation Toolbox ... science ecosystem. MLaut automates large-scale evaluation and benchmarking of machine learning algorithms...
  • NiaAML

  • Referenced in 1 article [sw38665]
  • NiaAML is an automated machine learning Python framework based on nature-inspired algorithms for optimization ... name comes from the automated machine learning method of the same name [1]. Its goal...
  • TacticToe

  • Referenced in 6 articles [sw28627]
  • HOL4 tactics. Techniques combining machine learning with translation to automated reasoning have recently become...
  • modelStudio

  • Referenced in 4 articles [sw30898]
  • Explanations for ML Predictive Models. Automate explanation of machine learning predictive models. This package generates...
  • Katib

  • Referenced in 1 article [sw37565]
  • Kubernetes-native project for automated machine learning (AutoML). Katib supports Hyperparameter Tuning, Early Stopping...
  • DeepHyper

  • Referenced in 4 articles [sw41119]
  • parallel computing to automate the design and development of machine learning (ML) models for scientific...
  • MizarMode

  • Referenced in 18 articles [sw01973]
  • methods and tools now include, e.g., the automated generation of proof skeletons, semantic browsing ... structured viewing, proof advice using trained machine learning tools like the Mizar Proof Advisor, deductive...
  • GenericWrapper4AC

  • Referenced in 4 articles [sw38659]
  • planning, scheduling, and machine learning (in particular deep learning). Automated algorithm configuration methods have recently...
  • Daikon

  • Referenced in 44 articles [sw04319]
  • executions. Dynamic invariant detection is a machine learning technique that can be applied to arbitrary ... test cases, predicting incompatibilities in component integration, automating theorem proving, repairing inconsistent data structures...
  • RSMTool

  • Referenced in 2 articles [sw29014]
  • educational natural language processing. Automated scoring engines employ machine learning models to predict scores ... text/audio of these responses. Examples of automated scoring engines include Project Essay Grade for written...