INVASE | wise Variable Selection - 2019 ICLR | Machine Learning library
kandi X-RAY | INVASE Summary
kandi X-RAY | INVASE Summary
INVASE is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. INVASE has no bugs, it has no vulnerabilities and it has low support. However INVASE build file is not available. You can download it from GitHub.
Authors: Jinsung Yoon, James Jordon, Mihaela van der Schaar. Paper: Jinsung Yoon, James Jordon, Mihaela van der Schaar, "IINVASE: Instance-wise Variable Selection using Neural Networks," International Conference on Learning Representations (ICLR), 2019. (This directory contains implementations of INVASE framework for the following applications. To run the pipeline for training and evaluation on INVASE framwork, simply run python3 -m main_inavse.py. Note that any model architecture can be used as the actor and critic models such as CNN. The condition for models is to have train and predict functions as its subfunctions.
Authors: Jinsung Yoon, James Jordon, Mihaela van der Schaar. Paper: Jinsung Yoon, James Jordon, Mihaela van der Schaar, "IINVASE: Instance-wise Variable Selection using Neural Networks," International Conference on Learning Representations (ICLR), 2019. (This directory contains implementations of INVASE framework for the following applications. To run the pipeline for training and evaluation on INVASE framwork, simply run python3 -m main_inavse.py. Note that any model architecture can be used as the actor and critic models such as CNN. The condition for models is to have train and predict functions as its subfunctions.
Support
Quality
Security
License
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Support
INVASE has a low active ecosystem.
It has 40 star(s) with 16 fork(s). There are 1 watchers for this library.
It had no major release in the last 6 months.
There are 0 open issues and 3 have been closed. On average issues are closed in 3 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of INVASE is current.
Quality
INVASE has 0 bugs and 0 code smells.
Security
INVASE has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
INVASE code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
INVASE 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
INVASE releases are not available. You will need to build from source code and install.
INVASE has no build file. You will be need to create the build yourself to build the component from source.
Installation instructions are not available. Examples and code snippets are available.
INVASE saves you 138 person hours of effort in developing the same functionality from scratch.
It has 345 lines of code, 16 functions and 4 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed INVASE and discovered the below as its top functions. This is intended to give you an instant insight into INVASE implemented functionality, and help decide if they suit your requirements.
- Generate dataset
- Generate the logit model
- Generate ground truth values
- Generate n random variables
- Train the critic
- Predict the model
- Bernoulli sampling
- Compute feature performance
- Compute the prediction performance
- Predict from the critic
- Compute the importance of a feature
Get all kandi verified functions for this library.
INVASE Key Features
No Key Features are available at this moment for INVASE.
INVASE Examples and Code Snippets
No Code Snippets are available at this moment for INVASE.
Community Discussions
Trending Discussions on INVASE
QUESTION
How to use selectInput to map a subset of a dataframe
Asked 2017-Nov-01 at 20:39
ANSWER
Answered 2017-Nov-01 at 20:39Do not know why you subset before you run the app.
I just build an example df (next time please provide a sample with dput())
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install INVASE
You can download it from GitHub.
You can use INVASE like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use INVASE like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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