modelselection | model assessment , model selection | Machine Learning library

by avehtari HTML Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | modelselection Summary

modelselection is a HTML library typically used in Artificial Intelligence, Machine Learning applications. modelselection has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Tutorial on model assessment, model selection and inference after model selection

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modelselection has a low active ecosystem.

It has 144 star(s) with 30 fork(s). There are 10 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of modelselection is current.

Quality

modelselection has 0 bugs and 0 code smells.

Security

modelselection has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

modelselection code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

modelselection does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

modelselection releases are not available. You will need to build from source code and install.

It has 948 lines of code, 0 functions and 1 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

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modelselection Key Features

No Key Features are available at this moment for modelselection.

modelselection Examples and Code Snippets

No Code Snippets are available at this moment for modelselection.

Community Discussions

Trending Discussions on modelselection

Using Self-Segmentation javascript of Mediapipe to pass user selfie as a texture on Networked-Aframe for multiplaying experiences

Django - Min/Max values not displaying on Index

QUESTION

Using Self-Segmentation javascript of Mediapipe to pass user selfie as a texture on Networked-Aframe for multiplaying experiences

Asked 2021-Sep-15 at 07:47

Well my target is to make a multiplaying 3D environment where the persons are represented by cubes that have as textures their selfie without the background. It is a kind of cheap virtual production without chroma key background. The background is removed with MediaPipe Selfie-Segmentation. The issue is that instead of having the other player texture on the cube (P1 should see P2, and P2 should see P1, each one sees his selfie. This means that P1 sees P1 and P2 sees P2 which is bad.

Live demo: https://vrodos-multiplaying.iti.gr/plain_aframe_mediapipe_testbed.html

Instructions: You should use two machines to test it Desktops, Laptops or Mobiles. Use only Chrome as Mediapipe is not working at other browsers. In case webpage jams, reload the webpage (Mediapipe is sometimes sticky). At least two machines should load the webpage in order to start the multiplaying environment.

Code:

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ANSWER

Answered 2021-Sep-15 at 07:47

Well, I found it. The problem was that a MediaStream can have many video tracks. See my answer here:

https://github.com/networked-aframe/networked-aframe/issues/269

Unfortunately networked-aframe EasyRtcAdapter does not support many MediaStreams, but it is easy to add another video track and then get videotrack[1] instead of videotrack[0]. I should make a special EasyRtcAdapter to avoid having two video tracks and avoid overstressing bandwidth.

Source https://stackoverflow.com/questions/68994847

QUESTION

Django - Min/Max values not displaying on Index

Asked 2020-Sep-14 at 00:13

I'm calculating the min and max values so I can display the spread of RRPs for a car model. Here I just have the min value, which is being calculated correctly but it will not display to the index file using the guidance I got from various examples/sites. Greatly appreciatte any help.

Models.py

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ANSWER

Answered 2020-Sep-14 at 00:13

In your views.py, you defined the key for the aggregate result, inside your context dictionary, as RRPView:

Source https://stackoverflow.com/questions/63863575

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install modelselection

You can download it from GitHub.

Support

Basics of predictive performance estimationWhen cross-validation is not needed Simple model we trust - betablockersWhen cross-validation is useful We don't trust the model - roaches Complex model with posterior dependencies - collinearOn accuracy of cross-validationCross-validation and hierarchical modelsWhen cross-validation is not enough large number of models - diabetesloo 2.0Projection predictive model selection collinear diabetes projpred

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