Skip to content

GitLab

  • Menu
Projects Groups Snippets
    • Loading...
  • Help
    • Help
    • Support
    • Community forum
    • Submit feedback
  • Sign in / Register
  • F FEDOT
  • Project information
    • Project information
    • Activity
    • Labels
    • Members
  • Repository
    • Repository
    • Files
    • Commits
    • Branches
    • Tags
    • Contributors
    • Graph
    • Compare
  • Issues 87
    • Issues 87
    • List
    • Boards
    • Service Desk
    • Milestones
  • Merge requests 1
    • Merge requests 1
  • CI/CD
    • CI/CD
    • Pipelines
    • Jobs
    • Schedules
  • Deployments
    • Deployments
    • Environments
    • Releases
  • Monitor
    • Monitor
    • Incidents
  • Packages & Registries
    • Packages & Registries
    • Package Registry
    • Container Registry
    • Infrastructure Registry
  • Analytics
    • Analytics
    • Value stream
    • CI/CD
    • Repository
  • Wiki
    • Wiki
  • Snippets
    • Snippets
  • Activity
  • Graph
  • Create a new issue
  • Jobs
  • Commits
  • Issue Boards
Collapse sidebar
  • ITMO-NSS-team
  • FEDOT
  • Issues
  • #312

Closed
Open
Created May 26, 2021 by Elizaveta Lutsenko@LizLutsenkoOwner

Investigate new data operations for feature engineering and ensembling

Created by: J3FALL

  • Add simple Ensembling methods, such as TopModel, WeightedEnsemble and AverageEnsemble
  • Discover the best practises of FE methods for classification/regression of table-like datasets
  • Perform the experiments with expert-based feature engineering as a separate DataOperation blocks
  • Think about special presets of models/operations for classification/regression
  • Try feature generation methods, for instance, like featuretools
Assignee
Assign to
Time tracking