MLaPP | Machine Learning : a Probabilistic Perspective

by okomestudio Python Version: Current License: No License

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

kandi X-RAY | MLaPP Summary

MLaPP is a Python library. MLaPP has no bugs, it has no vulnerabilities and it has low support. However MLaPP build file is not available. You can download it from GitHub.

Machine Learning: a Probabilistic Perspective.

Support

Quality

Security

License

Reuse

Support

MLaPP has a low active ecosystem.

It has 0 star(s) with 2 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

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

It has a neutral sentiment in the developer community.

The latest version of MLaPP is current.

Quality

MLaPP has 0 bugs and 0 code smells.

Security

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

MLaPP code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

MLaPP 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

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

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

It has 241 lines of code, 10 functions and 14 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Fits the Gaussian model .
This function is used to plot the articles of the article .
Load a data file .
Predict class probabilities for a given model .
Normalize data .
Compute the class features for binary classification .
Generate a Gauss - Gaussian distribution .
Zero - one loss function .

Get all kandi verified functions for this library.

MLaPP Key Features

No Key Features are available at this moment for MLaPP.

MLaPP Examples and Code Snippets

No Code Snippets are available at this moment for MLaPP.

Community Discussions

Trending Discussions on MLaPP

R2020b: App Designer says can't open File MATLAB failing if condition

Passing Ajax Request to Django View on Multiple Button Click

QUESTION

R2020b: App Designer says can't open File MATLAB failing if condition

Asked 2020-Nov-27 at 19:30

How to solve this

C:\Users\SHUBHAM\Documents\MATLAB\Dymola_App.mlapp: Can't open file.

What I did is:

I created a GUI in MATLAB using AppDesigner

When I click Run it says that "C:\Users\SHUBHAM\Documents\MATLAB\Dymola_App.mlapp: Can't open file."

After close look I see that it is due to if condition

This is failing

This is working

...

ANSWER

Answered 2020-Nov-27 at 19:30

Nested if condition worked but dont know why that failed!

Source https://stackoverflow.com/questions/64795052

QUESTION

Passing Ajax Request to Django View on Multiple Button Click

Asked 2020-Aug-11 at 14:21

I'm trying to Pass data to View with two Click events with Ajax Post, everything goes well, when I have only one Button event (click event), but when I added the second click event I'm getting and error

If there is a need of more reference please let me know.

Template (With Two Buttons and Two dropdowns)

...

ANSWER

Answered 2020-Aug-11 at 14:21

Here's why request.POST.get() works:

It would be natural to just use request.POST['plot1'] at first. However, what happens in this case is that if plot1 doesn't exist, it will raise a KeyError which is what happened in your case.

The solution is to use request.POST.get('plot1', False) this method allows you to specify a default parameter to be used if 'plot1 doesn't exist. False is the default parameter in this case.

Source https://stackoverflow.com/questions/63195201

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

Vulnerabilities

No vulnerabilities reported

Install MLaPP

You can download it from GitHub.
You can use MLaPP 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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