ML-lib | An extensive machine learning library , made from scratch | Machine Learning library

 by   christopherjenness Python Version: Current License: MIT

kandi X-RAY | ML-lib Summary

kandi X-RAY | ML-lib Summary

ML-lib is a Python library typically used in Artificial Intelligence, Machine Learning applications. ML-lib 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.

This is a machine learning library, made from scratch.
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            kandi-support Support

              ML-lib has a low active ecosystem.
              It has 104 star(s) with 20 fork(s). There are 5 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 7 open issues and 1 have been closed. On average issues are closed in 321 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of ML-lib is current.

            kandi-Quality Quality

              ML-lib has 0 bugs and 0 code smells.

            kandi-Security Security

              ML-lib has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              ML-lib code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              ML-lib is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              ML-lib 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.

            Top functions reviewed by kandi - BETA

            kandi has reviewed ML-lib and discovered the below as its top functions. This is intended to give you an instant insight into ML-lib implemented functionality, and help decide if they suit your requirements.
            • Fit the model
            • Compute the model
            • Add a layer to the layer
            • Adds a new RegressionTree
            • Fits the tree
            • Calculate the prediction of the tree
            • Add a new regression tree
            • Run locallogistic regression
            • Logistic function
            • Creates the locallogistic Hessian
            • Predict class for each class
            • Compute the DANN distance between two points
            • Compute the weights of the solution
            • Performs gradient descent using gradient descent
            • Return the classval for the given variable
            • Gradient of the logistic function
            • Add a cut
            • Compute the mean value for each node
            • Compute the covariance matrix
            • Train the model
            • Predicts the logistic function
            • Fit a function to the model
            • Estimate the gradient descent
            • Gradient descent
            • Uses Newtons Method
            • Compute the class variance for each node
            Get all kandi verified functions for this library.

            ML-lib Key Features

            No Key Features are available at this moment for ML-lib.

            ML-lib Examples and Code Snippets

            No Code Snippets are available at this moment for ML-lib.

            Community Discussions

            QUESTION

            cpan module install failed, no prereqs missing
            Asked 2022-Mar-04 at 22:01

            Just trying to install a CPAN module, don't seem to be missing any prereqs, and can't seem to find anything that points to what I need to do to fix this. Can someone make sense of what the issue might be? I'd rather not force install unless I'm absolutely sure its maybe just an issue with the tests. I've looked at previous questions and the issue is almost always a missing prereq module but doesn't seem to be the case here.

            ...

            ANSWER

            Answered 2022-Mar-04 at 22:01

            There are two bugs in XML-Liberal-0.30.

            Forcing the installation of the module is not recommended.

            This will install the distribution:

            Source https://stackoverflow.com/questions/71351244

            QUESTION

            Unable to get XML::LibXML to install Mac OS11
            Asked 2020-Dec-08 at 20:31

            I've been trying to get XML::LibXML to install on perl for a few days, and I think I've run into a wall regarding what to try next. As I understand it XML::LibXML needs to know where Libxml2 is located. I've installed Libxml2 with Homebrew, but it installs a keg-only, so my perl install doesn't know where to find it. What is the command that I need to add to my .bash_profile file so perl know where to look? I've tried using both perlbrew and Activeperl, and the results are the same.

            ...

            ANSWER

            Answered 2020-Dec-08 at 20:31

            The following worked for me on macOS 10.15.5, using perlbrew with Perl version 5.30.1.

            Source https://stackoverflow.com/questions/65205664

            QUESTION

            How can i fix Onnxruntime session->Run problem?
            Asked 2020-Sep-03 at 21:17

            I am trying to write a wrapper for onnxruntime. The model receives one tensor as an input and one tensor as an output. During session->Run, a segmentation error occurs inside the onnxruntime library. Both downloaded library and built from source throw the same error.

            Here is error:

            ...

            ANSWER

            Answered 2020-Sep-03 at 21:17

            I do not have the complete idea of your code structure but try making Ort::Env variable static.

            Source https://stackoverflow.com/questions/62787710

            QUESTION

            JSTL XML in JSF Facelet
            Asked 2020-Feb-22 at 20:06

            I am trying to create a composite component in JSF Facelets 1.2.8. The component is supposed to be a table optimised to work with the jquery jstree framework for presenting a table as a directory tree.

            The component is supposed to accept an attribute containing a xml value, which represents the structure of the tree. In Order to prepare the component for the presentation as file tree I want to parse the xml data in the components xhtml file.

            For this I want to use the JSTL-XML-Taglibrary but it seems like it cant be found. This is how my namespace declaration looks like:

            ...

            ANSWER

            Answered 2020-Feb-22 at 20:06

            The JSTL XML (and SQL) taglibs are considered bad practices and are "officious" deprecated since JSP 2.0 (2003) wherein the MVC approach was strongly preferred and advocated over tight-coupling the controller and the model into the view. Facelets, which was introduced a bit later (2005), has even no support for JSTL XML and SQL taglibs at all. Only JSTL core and functions are supported.

            If you're absolutely positive that you need to massage a XML file into a XHTML file, then better use XSL instead. You can find a kickoff example here: How to create dynamic JSF form fields.

            See also:

            Source https://stackoverflow.com/questions/60337761

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

            Vulnerabilities

            No vulnerabilities reported

            Install ML-lib

            You can download it from GitHub.
            You can use ML-lib 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

            Support vector machines maximize the margins between classesUsing kernels, support vector machines can produce non-linear decision boundries. The RBF kernel is shown belowAn alternative learning algorithm, the perceptron, can linearly separate classes. It does not maximize the margin, and is severely limited.
            Find more information at:

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            https://github.com/christopherjenness/ML-lib.git

          • CLI

            gh repo clone christopherjenness/ML-lib

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            git@github.com:christopherjenness/ML-lib.git

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