mlpack | mlpack : a fast , header-only C++ machine | Machine Learning library

 by   mlpack C++ Version: 4.3.0.post1 License: Non-SPDX

kandi X-RAY | mlpack Summary

kandi X-RAY | mlpack Summary

mlpack is a C++ library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. mlpack has no bugs, it has no vulnerabilities and it has medium support. However mlpack has a Non-SPDX License. You can download it from GitHub.

The mlpack website can be found at and it contains numerous tutorials and extensive documentation. This README serves as a guide for what mlpack is, how to install it, how to run it, and where to find more documentation. The website should be consulted for further information:.
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              mlpack has a medium active ecosystem.
              It has 4421 star(s) with 1503 fork(s). There are 183 watchers for this library.
              There were 2 major release(s) in the last 6 months.
              There are 28 open issues and 1501 have been closed. On average issues are closed in 88 days. There are 11 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of mlpack is 4.3.0.post1

            kandi-Quality Quality

              mlpack has no bugs reported.

            kandi-Security Security

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

            kandi-License License

              mlpack has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

            kandi-Reuse Reuse

              mlpack releases are available to install and integrate.
              Installation instructions are not available. Examples and code snippets are available.

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            mlpack Key Features

            No Key Features are available at this moment for mlpack.

            mlpack Examples and Code Snippets

            No Code Snippets are available at this moment for mlpack.

            Community Discussions

            QUESTION

            How to serialize sparse matrix in Armadillo and use with mpi implementation of boost?
            Asked 2021-Apr-27 at 12:30

            I've been trying to serialize the sparse matrix from armadillo cpp library. I am doing some large-scale numerical computations, in which the data get stored in a sparse matrix, which I'd like to gather using mpi(Boost implementation) and sum over the matrices coming from different nodes. I'm stuck right now is how to send the sparse matrix from one node to other nodes. Boost suggests that to send user-defined objects (SpMat in this case) it needs to be serialized.

            Boost's documentation gives a good tutorial on how to serialize a user-defined type and I can serialize some basic classes. Now, armadillo's SpMat class is very complicated for me to understand, and serialize.

            I've come across few questions and their very elegant answers

            1. This answer by Ryan Curtin the co-author of Armadillo and author of mlpack has shown a very elegant way to serialize the Mat class.
            2. This answer by sehe shows a very simple way to serialize sparse matrix.

            Using the first I can mpi::send a Mat class to another node in the communicator, but using the latter I couldn't do mpi::send.

            This is adapted from the second linked answer

            ...

            ANSWER

            Answered 2021-Apr-27 at 12:30

            I hate to say so, but that answer by that sehe guy was just flawed. Thanks for finding it.

            The problem was that it didn't store the number of non-zero cells during serialization. Oops. I don't know how I overlooked this when testing.

            (Looks like I had several versions and must have patched together a Frankenversion of it that wasn't actually properly tested).

            I also threw in a test the matrix is cleared (so that if you deserialize into an instance that had the right shape but wasn't empty you don't end up with a mix of old and new data.)

            FIXED

            Source https://stackoverflow.com/questions/67267414

            QUESTION

            Armadillo Exception Thrown when using mlpack
            Asked 2020-Dec-10 at 05:11

            I'm using the mlpack library which runs on top of the Armadillo linear algebra library. An exception has been thrown referring to the line in the debug.hpp file as shown below:

            ...

            ANSWER

            Answered 2020-Dec-10 at 05:11

            Try installing the x64 and x86 re-distributable for visual studio 2015, if you don't have them.

            If it still doesn't work it check the compilation settings: either you need static compiling with /MT flag or dynamic compile with /MD flag.

            This flag is under Project properties/ C/C++ / Code generation.

            Source https://stackoverflow.com/questions/63887258

            QUESTION

            Building MLPack from C++ source using CMake: is Julia required?
            Asked 2020-Feb-16 at 15:39

            I am trying to build MLPack from its C++ source using CMake, and for some reason it is complaining that it can't find Julia.

            CMake Error at /usr/local/Cellar/cmake/3.14.5/share/cmake/Modules/FindPackageHandleStandardArgs.cmake:137 (message): Julia not found (missing: JULIA_EXECUTABLE) (Required is at least version "0.7.0")

            Has anyone encountered a similar issue? On the MLPack build instructions, there is no mention of Julia being a required package.

            Thanks, Amine

            ...

            ANSWER

            Answered 2020-Feb-16 at 15:39

            MLPack has Julia bindings that are set to build by default (see the CMake source). The CMake option is shown on the main GitHub README page. You can disable the Julia bindings build using the BUILD_JULIA_BINDINGS variable:

            Source https://stackoverflow.com/questions/60248656

            QUESTION

            Cmake Mlpack Ubuntu Issue
            Asked 2020-Jan-19 at 11:32

            I'm using cmake in VSC on Ubuntu for a simple data cluster algorithm. For this I want to use the already existing Mlpack library. If I try to run my code I receive errors like this

            main.cpp:(.text._ZN6mlpack8neighbor14NeighborSearchINS0_19NearestNeighborSortENS_6metric7LMetricILi1ELb0EEEN4arma3MatIdEENS_4tree6KDTreeENS9_15BinarySpaceTreeIS5_NS0_18NeighborSearchStatIS2_EES8_NS_5bound10HRectBoundENS9_13MidpointSplitEE17DualTreeTraverserENSH_19SingleTreeTraverserEE6SearchEmRNS7_ImEERS8_[_ZN6mlpack8neighbor14NeighborSearchINS0_19NearestNeighborSortENS_6metric7LMetricILi1ELb0EEEN4arma3MatIdEENS_4tree6KDTreeENS9_15BinarySpaceTreeIS5_NS0_18NeighborSearchStatIS2_EES8_NS_5bound10HRectBoundENS9_13MidpointSplitEE17DualTreeTraverserENSH_19SingleTreeTraverserEE6SearchEmRNS7_ImEERS8_]+0x6b4): Warnung: undefinierter Verweis auf »mlpack::Log::Info«

            This seems to be an error because of false linking to Mlpack. I followed this example Getting Started with mlpack and created my own CmakeLists file

            ...

            ANSWER

            Answered 2020-Jan-14 at 09:11

            Just install mlpack in your system and use FindMLPACK.cmake provided in mlpack models repo. Your root CMakeLists.txt should look like this:

            Source https://stackoverflow.com/questions/59729745

            QUESTION

            using distance metric in MLpack
            Asked 2019-Sep-10 at 00:34

            I want to use ML pack distance metrics to evaluate distance.

            I have two arma:vec. Need to find distance between the two vec.

            mlpack::metric::EuclideanDistance distance();

            ...

            ANSWER

            Answered 2019-Sep-10 at 00:34

            mlpack::metric::EuclideanDistance distance;

            instead of

            mlpack::metric::EuclideanDistance distance();

            works

            Source https://stackoverflow.com/questions/57862576

            QUESTION

            OCamlbuild recursively build dependecies
            Asked 2019-Sep-02 at 10:08

            I’m building a project that uses OCamlbuild as its build system. This project also requires a library, which also uses OCamlbuild. This library comes with .mlpack, _tags, and myocamlbuild.ml files. I have included the library into my project as a git submodule in the path lib/mylib starting from the project’s root.

            I’d like to tell OCamlbuild to recursively compile the library, as I would to with a make -C lib/mylib in a Makefile.

            How can I achieve that?

            Thanks.

            ...

            ANSWER

            Answered 2019-Sep-02 at 10:08

            An answer is described in Working on dependent projects with OCamlbuild.
            Basically, add : include to _tags and import the library myocamlbuild.ml. It does seem a bit wobbly.

            Or use Dune.

            Source https://stackoverflow.com/questions/53694865

            QUESTION

            I can't build mlpack?
            Asked 2018-Nov-06 at 08:12

            I am working on mlpack library (C++ machine learning library). I followed the steps of keon here: building mlpack, but i got the following error in cmd ,when i reached the last step which is building mlpack:

            ...

            ANSWER

            Answered 2017-Jan-23 at 14:05

            You must have messed up your armadillo installation, to be more specific, you didn't specify the armadillo include dirs.

            According to this more detailed instruction, point 10:

            Specify the path of the libraries, dll and setup some definition, the details can found at here

            So, you can try and add these lines to your mlpack's CMakeLists.txt:

            set(ARMADILLO_LIBRARY "C:/Users/yyyy/Qt/3rdLibs/armadillo/armadillo-5.600.2/vc2015_build/bin/vc2015_x86_amd64/release") set(ARMADILLO_INCLUDE_DIR "C:/Users/yyyy/Qt/3rdLibs/armadillo/armadillo-5.600.2/include")

            Source https://stackoverflow.com/questions/41807194

            QUESTION

            undefined symbol in Cython module when using mlpack
            Asked 2018-Apr-11 at 15:03

            I met the problem "undefined symbol" when using mlpack in Cython. Here is my test case:

            ...

            ANSWER

            Answered 2018-Apr-11 at 15:03

            The extension must be linked to the library it is using.

            Source https://stackoverflow.com/questions/49777638

            QUESTION

            How can I use mlpack in Cython?
            Asked 2018-Mar-29 at 18:22

            I downloaded the source files, but I don't know how to combine it with Cython. Is there a Cython wrapper for mlpack?

            ...

            ANSWER

            Answered 2018-Mar-29 at 18:22

            mlpack's build infrastructure will automatically generate Cython bindings; all you need to do is the usual build instructions:

            Source https://stackoverflow.com/questions/49314952

            QUESTION

            Intel compiler in visual studio not finding boost libraries
            Asked 2017-Apr-17 at 18:45

            I am trying to install mlpack in vs2013. msvc2013 is not compatible, so I am using Intel C++ compiler XE 14.0. However, Intel compiler is not finding the boost libraries.

            Using only MSVC -

            ...

            ANSWER

            Answered 2017-Apr-17 at 18:45

            Currently, Boost NuGet packages do not have binaries for Intel compiler. Boost NuGet package contains binaries from the Prebuilt windows binaries only. In the future, I'm happy to add new binaries as soon as they are available to download from some trusted resource.

            Source https://stackoverflow.com/questions/42534470

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

            Vulnerabilities

            No vulnerabilities reported

            Install mlpack

            You can download it from GitHub.

            Support

            The documentation given here is only a fraction of the available documentation for mlpack. If doxygen is installed, you can type make doc to build the documentation locally. Alternately, up-to-date documentation is available for older versions of mlpack:. To learn about the development goals of mlpack in the short- and medium-term future, see the vision document.
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            Install
          • PyPI

            pip install mlpack

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            https://github.com/mlpack/mlpack.git

          • CLI

            gh repo clone mlpack/mlpack

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            git@github.com:mlpack/mlpack.git

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