UCI-Data-Analysis | data hosted on UCI Machine Learning Archives | Machine Learning library

by rupakc Python Version: Current License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | UCI-Data-Analysis Summary

UCI-Data-Analysis is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning applications. UCI-Data-Analysis has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However UCI-Data-Analysis build file is not available. You can download it from GitHub.

Repository for Analysis of data hosted on UCI Machine Learning Archives

Support

Quality

Security

License

Reuse

Support

UCI-Data-Analysis has a low active ecosystem.

It has 15 star(s) with 42 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 1 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of UCI-Data-Analysis is current.

Quality

UCI-Data-Analysis has no bugs reported.

Security

UCI-Data-Analysis has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

UCI-Data-Analysis is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

UCI-Data-Analysis releases are not available. You will need to build from source code and install.

UCI-Data-Analysis 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 UCI-Data-Analysis and discovered the below as its top functions. This is intended to give you an instant insight into UCI-Data-Analysis implemented functionality, and help decide if they suit your requirements.

Plot the accuracy bar chart .
Visualize SNE .
Plot classification boundaries .
Preprocess a sentence .
Test for Cross Validation Method
Remove punctuation from a tokenized summary .
Split a train test set .
Convert a list of names to a string .
Recursive recursive feature selector .
Recursive feature selector function .

Get all kandi verified functions for this library.

UCI-Data-Analysis Key Features

No Key Features are available at this moment for UCI-Data-Analysis.

UCI-Data-Analysis Examples and Code Snippets

No Code Snippets are available at this moment for UCI-Data-Analysis.

Community Discussions

Trending Discussions on UCI-Data-Analysis

minepy: Buffer has wrong number of dimensions

QUESTION

minepy: Buffer has wrong number of dimensions

Asked 2018-Apr-26 at 20:32

I am trying to use Maximal information coefficient in jupyter notebook, with the Boston Housing dataset.

...

ANSWER

Answered 2018-Apr-26 at 20:32

I don't know too much about minepy but viewing the source code, compute_score receive x and y parameters which must be 1D arrays, then if you pass a 14xN array (2D) this wont work.

Instead pstats (View on API) receives a 2D array and cstats(View on API) receives a pair of 2D arrays, so you can take a look of both, as mentioned, I don't know about minepy too much or the purpose that you are looking for, but you can use them as follows:

Source https://stackoverflow.com/questions/50030665

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

Vulnerabilities

No vulnerabilities reported

Install UCI-Data-Analysis

You can download it from GitHub.
You can use UCI-Data-Analysis 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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