auto-evaluation | Python package to auto generate model evaluation report | Machine Learning library

by LenzDu Python Version: Current License: MIT

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

kandi X-RAY | auto-evaluation Summary

auto-evaluation is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning applications. auto-evaluation has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Python package to auto generate model evaluation report

Support

Quality

Security

License

Reuse

Support

auto-evaluation has a low active ecosystem.

It has 4 star(s) with 0 fork(s). There are no watchers for this library.

It had no major release in the last 6 months.

There are 1 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 auto-evaluation is current.

Quality

auto-evaluation has no bugs reported.

Security

auto-evaluation has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

auto-evaluation is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

auto-evaluation releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed auto-evaluation and discovered the below as its top functions. This is intended to give you an instant insight into auto-evaluation implemented functionality, and help decide if they suit your requirements.

Generate the report
Plot the threshold trend
Plot the precision recall curve
Get the table of the confusion matrix
Plot a stacked histogram
Plot the ROC curve
Gets the statistics for the model
Aggregate plot
Plot histogram
Returns a pandas DataFrame containing the thresholds of the fit
Render the overview table and tabs
Segment of the fit
Aggregate the plot
Convert a matplotlib figure to a base64 string
Plots the classification counts of the class
Plot the confusion matrix
Fit the model
Check if Y is a numpy array
Record the evaluation

Get all kandi verified functions for this library.

auto-evaluation Key Features

No Key Features are available at this moment for auto-evaluation.

auto-evaluation Examples and Code Snippets

No Code Snippets are available at this moment for auto-evaluation.

Community Discussions

Trending Discussions on auto-evaluation

core.js:10101 NG0303: Can't bind to 'matCellDefOf' since it isn't a known property of 'td'

How to Append Laravel Collection Query Results

QUESTION

core.js:10101 NG0303: Can't bind to 'matCellDefOf' since it isn't a known property of 'td'

Asked 2021-May-26 at 23:55

i'm trying to use Mat table from angular material, so the console shows an error as you see in this picture

core.js:10101 NG0303: Can't bind to 'matCellDefOf' since it isn't a known property of 'td'. enter image description here

and here's code

...

ANSWER

Answered 2021-May-26 at 23:55

Ok I could reproduce the issue in stackblitz example the proble is that, you have several lines in your template

Source https://stackoverflow.com/questions/67713674

QUESTION

How to Append Laravel Collection Query Results

Asked 2021-Mar-25 at 11:03

I have the query below:

...

ANSWER

Answered 2021-Mar-25 at 09:28

First dd($controls_checklist); and verify that in the place of $controls_checklist->id the id actually exists. If not change the foreach loop statement.

Coming to foreach loop, try using the model with join or innerjoin to manage the query result

Thank you

Source https://stackoverflow.com/questions/66796169

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

Vulnerabilities

No vulnerabilities reported

Install auto-evaluation

Clone the git repo, navigate into the repo directory and use pip to install.

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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