mmit | Regression trees for interval censored output data | Machine Learning library

by aldro61 Python Version: v1.1.1 License: GPL-3.0

X-Ray Key Features Code Snippets(2)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | mmit Summary

mmit is a Python library typically used in Artificial Intelligence, Machine Learning applications. mmit has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

Regression trees for interval censored output data

Support

Quality

Security

License

Reuse

Support

mmit has a low active ecosystem.

It has 6 star(s) with 6 fork(s). There are 2 watchers for this library.

It had no major release in the last 12 months.

There are 4 open issues and 6 have been closed. On average issues are closed in 286 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of mmit is v1.1.1

Quality

mmit has 0 bugs and 0 code smells.

Security

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

mmit code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

mmit is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

mmit releases are available to install and integrate.

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

Installation instructions, examples and code snippets are available.

It has 1050 lines of code, 110 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 mmit and discovered the below as its top functions. This is intended to give you an instant insight into mmit implemented functionality, and help decide if they suit your requirements.

Fit the decision trees to the estimator
Perform minimum cost complexity pruning
Return True if two floats are greater than
Return True if two floats are equal
Return True if floats are greater than b
Evaluate on a dataset
Fits the hyperparameters
Predict using the best estimator
Mean squared error
Check X and y and y
Compute the mean squared error
Predict for the model
Predict the predicted value for each example
Compute the best estimator score
Find all datasets in path

Get all kandi verified functions for this library.

mmit Key Features

No Key Features are available at this moment for mmit.

mmit Examples and Code Snippets

Maximum margin Interval Trees,R package installation and usage

Python

Lines of Code : 2

License : Strong Copyleft (GPL-3.0)

Copy

if(!require(devtools))install.package("devtools")
devtools::install_github("aldro61/mmit/Rpackage")

Maximum margin Interval Trees,Python package installation and usage

Python

Lines of Code : 1

License : Strong Copyleft (GPL-3.0)

Copy

python setup.py install

Community Discussions

Trending Discussions on mmit

Rails - NoMethodError (undefined method 'permit' for "reps":string)

QUESTION

Rails - NoMethodError (undefined method 'permit' for "reps":string)

Asked 2017-Jan-14 at 22:27

So I'm trying to create multiple objects from a single form in Rails 5. This was working perfectly fine in rails 4.2, I'm not exactly sure what is causing the error (I imagine it has something to do with the view).

Another problem I've run into after upgrading to rails 5 is now my form is only submitting the last record. I used this walkthrough for reference: http://vicfriedman.github.io/blog/2015/07/18/create-multiple-objects-from-single-form-in-rails/

This is the input and here are the parameters I'm sending.

...

ANSWER

Answered 2017-Jan-14 at 19:45

You need to add .require(:exercise) (I am assuming your model's name is exercise) to use strong params.

Requiring will enable your app to give error if you don't pass the model. Because the parameters you are whitelisting are defined for that model.

Just replace

Source https://stackoverflow.com/questions/41654140

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

Vulnerabilities

No vulnerabilities reported

Install mmit

The source code of the mmit Python package is located in the mmit sub-directory, and can be installed via the following command. The package includes a scikit-learn style class to learn Maximum Margin Interval Trees.
The source code of the mmit R package is located in the Rpackage sub-directory, and can be installed via the following R commands. The package currently provides an interface for the dynamic programming algorithm used to train Maximum Margin Interval Trees. Support for learning trees in R will be implemented in the near future.

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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