inlineint
Joined 11 years ago
Joined 11 years ago
Prepare two equally sized ensembles of classifiers, let's call them A and B.
1. Train each classifier in ensemble A on labelled data to predict does a picture contains a cat.
2. Take some other unlabelled dataset and collect answers from classifiers from A for each picture from this dataset.
3. Train each classifier in ensemble B to predict average answer of classifiers from A for each picture from the unlabelled dataset.
Then for a picture from the test dataset it would be possible to get answers from ensemble A and from ensemble B and calculate what would be the surprisingly popular answer.
I wish there was an open standard for operations that hub allows to do and all major Git forges [1], including open source ones, such as Gogs/Gitea and GitLab, supported it. In that case having a command-line tool that, like Git itself, is not tied to a particular vendor, but allows to do what hub does, could have been indispensable.
There is CommonMark specification: https://commonmark.org.
Remote: Yes
Willing to relocate: No
Technologies: C++, Java, Python, JavaScript/TypeScript.
Résumé/CV: https://docs.google.com/document/d/1zg9bD8jXTI1OHVvQYvEwhsIc...
Email: Available in the resume