tr | Better Generalization by Efficient Trust Region Method
kandi X-RAY | tr Summary
kandi X-RAY | tr Summary
tr is a Python library. tr has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However tr build file is not available. You can download it from GitHub.
code for Better Generalization by Efficient Trust Region Method, Liu et al. 2018.
code for Better Generalization by Efficient Trust Region Method, Liu et al. 2018.
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Quality
Security
License
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Support
tr has a low active ecosystem.
It has 3 star(s) with 2 fork(s). There are 1 watchers for this library.
It had no major release in the last 6 months.
tr has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of tr is current.
Quality
tr has no bugs reported.
Security
tr has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
tr is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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tr releases are not available. You will need to build from source code and install.
tr has no build file. You will be need to create the build yourself to build the component from source.
Top functions reviewed by kandi - BETA
kandi has reviewed tr and discovered the below as its top functions. This is intended to give you an instant insight into tr implemented functionality, and help decide if they suit your requirements.
- Train the other function
- Compute accuracy
- Calculate the loss function
- Train the network
- Calculate the approximation of the loss function
- Iteratively compute the gradient of a function
- Plots the SDS Density
- Function to logarithm function
- Create a STHN model
- Make a list of convolutional layers
- Calculate the gradient for the loss function
- Read a csv file
- Parse the data file
- Reads the csv file
- Plots the tr gradient of the trd
- Calculate the total loss function
- Calculate the accuracy of each variable
- Calculate the Hessian
- Test network
- Test the Densenet test
Get all kandi verified functions for this library.
tr Key Features
No Key Features are available at this moment for tr.
tr Examples and Code Snippets
No Code Snippets are available at this moment for tr.
Community Discussions
No Community Discussions are available at this moment for tr.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install tr
You can download it from GitHub.
You can use tr 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 tr 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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