nnplot | python scripts for plotting various neural network | Data Visualization library

by osh Python Version: Current License: No License

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kandi X-RAY | nnplot Summary

nnplot is a Python library typically used in Analytics, Data Visualization, Tensorflow applications. nnplot has no bugs, it has no vulnerabilities and it has low support. However nnplot build file is not available. You can download it from GitHub.

python script for plotting various neural network architectures. for now, edit the "io" and "layers" variables in nnplot.py. Some example output ...

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nnplot has a low active ecosystem.

It has 9 star(s) with 4 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

nnplot has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of nnplot is current.

Quality

nnplot has 0 bugs and 0 code smells.

Security

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

nnplot code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

nnplot 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.

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

nnplot has no build file. You will be need to create the build yourself to build the component from source.

It has 59 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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nnplot Key Features

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nnplot Examples and Code Snippets

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Community Discussions

Trending Discussions on nnplot

K-fold cross validation modification to generated ANN code?

QUESTION

K-fold cross validation modification to generated ANN code?

Asked 2017-Aug-29 at 00:45

My data set is basically a matrix of 3 variables (input), and a matrix of 1 variable (target). There are 50 total data sets for each of these (basically 50 samples of f(x,y,z) = t)

I have only done the ANN training using the GUI. Never really with the script/code.

My most simple objective now is to split the data manually for each train-test run, so I can just painstakingly run the neural network 5 times, but I'm not even sure how to manually select a range of the data set for use in training, and which one for testing.

Here's the full exported script from MATLAB. The point of focus is shown below the wall of code.

...

ANSWER

Answered 2017-Aug-28 at 20:50

Network Parameters

The process of splitting the data into training, validation and test sets happens in the section that you identified. I'm just going to break down each of the lines. Starting with:

Source https://stackoverflow.com/questions/45924100

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

Vulnerabilities

No vulnerabilities reported

Install nnplot

You can download it from GitHub.
You can use nnplot 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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