diff --git a/README.md b/README.md index f82a2aee42..77e6545ac3 100644 --- a/README.md +++ b/README.md @@ -6,9 +6,11 @@ src="https://cdn.rawgit.com/mlpack/mlpack.org/e7d36ed8/mlpack-black.svg" style="
Home | - Documentation | - Community | - Help | + Documentation | + Doxygen +| + Community | + Help | IRC Chat
@@ -46,15 +48,16 @@ Python bindings. ### 1. Introduction -The mlpack website can be found at http://www.mlpack.org 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 +The mlpack website can be found at http://www.mlpack.org 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: - [mlpack homepage](http://www.mlpack.org/) - - [Tutorials](http://www.mlpack.org/docs/mlpack-git/doxygen/tutorials.html) + - [mlpack documentation](http://www.mlpack.org/docs.html) + - [Tutorials](http://www.mlpack.org/doc/mlpack-git/doxygen/tutorials.html) - [Development Site (Github)](http://www.github.com/mlpack/mlpack/) - - [API documentation](http://www.mlpack.org/docs/mlpack-git/doxygen/index.html) + - [API documentation (Doxygen)](http://www.mlpack.org/doc/mlpack-git/doxygen/index.html) ### 2. Citation details @@ -116,8 +119,8 @@ a PPA or other non-official sources, or installing with a manual build. There are some other useful pages to consult in addition to this section: - - [Building mlpack From Source](http://www.mlpack.org/docs/mlpack-git/doxygen/build.html) - - [Building mlpack From Source on Windows](http://www.mlpack.org/docs/mlpack-git/doxygen/build_windows.html) + - [Building mlpack From Source](http://www.mlpack.org/doc/mlpack-git/doxygen/build.html) + - [Building mlpack From Source on Windows](http://www.mlpack.org/doc/mlpack-git/doxygen/build_windows.html) mlpack uses CMake as a build system and allows several flexible build configuration options. One can consult any of numerous CMake tutorials for @@ -167,7 +170,7 @@ Options are specified with the -D flag. The allowed options include: USE_OPENMP=(ON/OFF): whether or not to use OpenMP if available Other tools can also be used to configure CMake, but those are not documented -here. See [this section of the build guide](http://www.mlpack.org/docs/mlpack-git/doxygen/build.html#build_config) +here. See [this section of the build guide](http://www.mlpack.org/doc/mlpack-git/doxygen/build.html#build_config) for more details, including a full list of options, and their default values. By default, command-line programs will be built, and if the Python dependencies @@ -292,13 +295,14 @@ documentation locally. Alternately, up-to-date documentation is available for older versions of mlpack: - [mlpack homepage](http://www.mlpack.org/) - - [Tutorials](http://www.mlpack.org/docs/mlpack-git/doxygen/tutorials.html) + - [mlpack documentation](http://www.mlpack.org/docs.html) + - [Tutorials](http://www.mlpack.org/doc/mlpack-git/doxygen/tutorials.html) - [Development Site (Github)](https://www.github.com/mlpack/mlpack/) - - [API documentation](http://www.mlpack.org/docs/mlpack-git/doxygen/index.html) + - [API documentation](http://www.mlpack.org/doc/mlpack-git/doxygen/index.html) ### 8. Bug reporting - (see also [mlpack help](http://www.mlpack.org/help.html)) + (see also [mlpack help](http://www.mlpack.org/questions.html)) If you find a bug in mlpack or have any problems, numerous routes are available for help. diff --git a/doc/guide/build_windows.hpp b/doc/guide/build_windows.hpp index 392c77546e..5bc9ab939f 100644 --- a/doc/guide/build_windows.hpp +++ b/doc/guide/build_windows.hpp @@ -60,7 +60,7 @@ The directories and paths used in this tutorial are just for reference purposes. and make sure you can use it from the Command Prompt (may need to add to the PATH) - Download the latest mlpack release from here: -mlpack +mlpack website @section build_windows_instructions Windows build instructions diff --git a/doc/guide/cli_quickstart.hpp b/doc/guide/cli_quickstart.hpp index 4cf5ab6a94..1518d4d9ac 100644 --- a/doc/guide/cli_quickstart.hpp +++ b/doc/guide/cli_quickstart.hpp @@ -108,17 +108,17 @@ Lots of other commands are available with different functionality. Below is a list of all the mlpack functionality offered through the command-line, split into some categories. - - Classification techniques: mlpack_adaboost, mlpack_decision_stump, mlpack_decision_tree, mlpack_hmm_train, mlpack_hmm_generate, mlpack_hmm_loglik, mlpack_hmm_viterbi, mlpack_hoeffding_tree, mlpack_logistic_regression, mlpack_nbc, mlpack_perceptron, mlpack_random_forest, mlpack_softmax_regression, mlpack_cf + - Classification techniques: mlpack_adaboost, mlpack_decision_stump, mlpack_decision_tree, mlpack_hmm_train, mlpack_hmm_generate, mlpack_hmm_loglik, mlpack_hmm_viterbi, mlpack_hoeffding_tree, mlpack_logistic_regression, mlpack_nbc, mlpack_perceptron, mlpack_random_forest, mlpack_softmax_regression, mlpack_cf - - Distance-based problems: mlpack_approx_kfn, mlpack_emst, mlpack_fastmks, mlpack_kfn, mlpack_knn, mlpack_krann, mlpack_lsh, mlpack_det, mlpack_range_search + - Distance-based problems: mlpack_approx_kfn, mlpack_emst, mlpack_fastmks, mlpack_kfn, mlpack_knn, mlpack_krann, mlpack_lsh, mlpack_det, mlpack_range_search - - Clustering: mlpack_kmeans, mlpack_mean_shift, mlpack_gmm_train, mlpack_gmm_generate, mlpack_gmm_probability, mlpack_dbscan + - Clustering: mlpack_kmeans, mlpack_mean_shift, mlpack_gmm_train, mlpack_gmm_generate, mlpack_gmm_probability, mlpack_dbscan - - Transformations: mlpack_pca, mlpack_radical, mlpack_local_coordinate_coding, mlpack_sparse_coding, mlpack_nca, mlpack_kernel_pca + - Transformations: mlpack_pca, mlpack_radical, mlpack_local_coordinate_coding, mlpack_sparse_coding, mlpack_nca, mlpack_kernel_pca - - Regression: mlpack_linear_regression, mlpack_lars + - Regression: mlpack_linear_regression, mlpack_lars - - Preprocessing/other: mlpack_preprocess_binarize, mlpack_preprocess_split, mlpack_preprocess_describe, mlpack_preprocess_imputer, mlpack_nmf + - Preprocessing/other: mlpack_preprocess_binarize, mlpack_preprocess_split, mlpack_preprocess_describe, mlpack_preprocess_imputer, mlpack_nmf For more information on what mlpack does, see http://www.mlpack.org/about.html. Next, let's go through another example for providing movie recommendations with @@ -200,7 +200,7 @@ easily plug into a data science production workflow for the command line. A great thing to do next would be to look at more documentation for the mlpack command-line programs: - - mlpack + - mlpack command-line program documentation Also, mlpack is much more flexible from C++ and allows much greater @@ -208,13 +208,13 @@ functionality. So, more complicated tasks are possible if you are willing to write C++. To get started learning about mlpack in C++, the following resources might be helpful: - - mlpack + - mlpack C++ tutorials - - mlpack + - mlpack build and installation guide - - Simple + - Simple sample C++ mlpack programs - - mlpack + - mlpack Doxygen documentation homepage */ diff --git a/doc/guide/python_quickstart.hpp b/doc/guide/python_quickstart.hpp index 71c0d90c5e..e9bc19db53 100644 --- a/doc/guide/python_quickstart.hpp +++ b/doc/guide/python_quickstart.hpp @@ -119,17 +119,17 @@ list of all the mlpack functionality offered through Python, split into some categories. - Classification techniques: adaboost(), decision_stump(), decision_tree(), hmm_train(), hmm_generate(), hmm_loglik(), hmm_viterbi(), hoeffding_tree(), logistic_regression(), nbc(), perceptron(), random_forest(), softmax_regression(), cf() + href="http://www.mlpack.org/doc/mlpack-git/python/adaboost.html">adaboost(), decision_stump(), decision_tree(), hmm_train(), hmm_generate(), hmm_loglik(), hmm_viterbi(), hoeffding_tree(), logistic_regression(), nbc(), perceptron(), random_forest(), softmax_regression(), cf() - - Distance-based problems: approx_kfn(), emst(), fastmks(), kfn(), knn(), krann(), lsh(), det() + - Distance-based problems: approx_kfn(), emst(), fastmks(), kfn(), knn(), krann(), lsh(), det() - - Clustering: kmeans(), mean_shift(), gmm_train(), gmm_generate(), gmm_probability() + - Clustering: kmeans(), mean_shift(), gmm_train(), gmm_generate(), gmm_probability() - - Transformations: pca(), radical(), local_coordinate_coding(), sparse_coding(), nca(), kernel_pca() + - Transformations: pca(), radical(), local_coordinate_coding(), sparse_coding(), nca(), kernel_pca() - - Regression: linear_regression(), lars() + - Regression: linear_regression(), lars() - - Preprocessing/other: preprocess_binarize(), preprocess_split(), preprocess_describe(), nmf() + - Preprocessing/other: preprocess_binarize(), preprocess_split(), preprocess_describe(), nmf() For more information on what mlpack does, see http://www.mlpack.org/about.html. Next, let's go through another example for providing movie recommendations with @@ -138,7 +138,7 @@ mlpack. @section python_quickstart_movierecs Using mlpack for movie recommendations In this example, we'll train a collaborative filtering model using mlpack's -cf() method. We'll train this on the MovieLens dataset from +cf() method. We'll train this on the MovieLens dataset from https://grouplens.org/datasets/movielens/, and then we'll use the model that we train to give recommendations. @@ -204,7 +204,7 @@ Now that you have done some simple work with mlpack, you have seen how it can easily plug into a data science workflow in Python. A great thing to do next would be to look at more documentation for the Python mlpack bindings: - - Python mlpack + - Python mlpack binding documentation Also, mlpack is much more flexible from C++ and allows much greater @@ -212,13 +212,13 @@ functionality. So, more complicated tasks are possible if you are willing to write C++ (or perhaps Cython). To get started learning about mlpack in C++, the following resources might be helpful: - - mlpack + - mlpack C++ tutorials - - mlpack + - mlpack build and installation guide - - Simple + - Simple sample C++ mlpack programs - - mlpack + - mlpack Doxygen documentation homepage */ diff --git a/doc/tutorials/README.md b/doc/tutorials/README.md index 500f1f31ee..fbfe04a169 100644 --- a/doc/tutorials/README.md +++ b/doc/tutorials/README.md @@ -1,41 +1,41 @@ ## Tutorials -Tutorials for mlpack can be found [here : mlpack tutorials](https://www.mlpack.org/docs/mlpack-git/doxygen/tutorials.html). +Tutorials for mlpack can be found [here : mlpack tutorials](https://www.mlpack.org/doc/mlpack-git/doxygen/tutorials.html). ### General mlpack tutorials These tutorials introduce the basic concepts of working with mlpack, aimed at developers who want to use and contribute to mlpack but are not sure where to start. -* [Building mlpack from source](http://www.mlpack.org/docs/mlpack-git/doxygen/build.html) -* [File Formats in mlpack](http://www.mlpack.org/docs/mlpack-git/doxygen/formatdoc.html) -* [Matrices in mlpack](http://www.mlpack.org/docs/mlpack-git/doxygen/matrices.html) -* [mlpack input and output](http://www.mlpack.org/docs/mlpack-git/doxygen/iodoc.html) -* [mlpack timers](http://www.mlpack.org/docs/mlpack-git/doxygen/timer.html) -* [Simple sample mlpack programs](http://www.mlpack.org/docs/mlpack-git/doxygen/sample.html) +* [Building mlpack from source](http://www.mlpack.org/doc/mlpack-git/doxygen/build.html) +* [File Formats in mlpack](http://www.mlpack.org/doc/mlpack-git/doxygen/formatdoc.html) +* [Matrices in mlpack](http://www.mlpack.org/doc/mlpack-git/doxygen/matrices.html) +* [mlpack input and output](http://www.mlpack.org/doc/mlpack-git/doxygen/iodoc.html) +* [mlpack timers](http://www.mlpack.org/doc/mlpack-git/doxygen/timer.html) +* [Simple sample mlpack programs](http://www.mlpack.org/doc/mlpack-git/doxygen/sample.html) ### Method-specific tutorials These tutorials introduce the various methods mlpack offers, aimed at users who want to get started quickly. These tutorials start with simple examples and progress to complex, extensible uses. -* [NeighborSearch tutorial (mlpack_knn / mlpack_kfn)](http://www.mlpack.org/docs/mlpack-git/doxygen/nstutorial.html) -* [LinearRegression tutorial (mlpack_linear_regression)](http://www.mlpack.org/docs/mlpack-git/doxygen/lrtutorial.html) -* [RangeSearch tutorial (mlpack_range_search)](http://www.mlpack.org/docs/mlpack-git/doxygen/rstutorial.html) -* [Density Estimation Trees tutorial (mlpack_det)](http://www.mlpack.org/docs/mlpack-git/doxygen/dettutorial.html) -* [K-Means tutorial (mlpack_kmeans)](http://www.mlpack.org/docs/mlpack-git/doxygen/kmtutorial.html) -* [FastMKS tutorial (mlpack_fastmks)](http://www.mlpack.org/docs/mlpack-git/doxygen/fmkstutorial.html) -* [Euclidean Minimum Spanning Trees tutorial (mlpack_emst)](http://www.mlpack.org/docs/mlpack-git/doxygen/emst_tutorial.html) -* [Alternating Matrix Factorization Tutorial](http://www.mlpack.org/docs/mlpack-git/doxygen/amftutorial.html) -* [Collaborative Filtering Tutorial](http://www.mlpack.org/docs/mlpack-git/doxygen/cftutorial.html) -* [Conventional Neural Evolution Tutorial](http://www.mlpack.org/docs/mlpack-git/doxygen/cnetutorial.html) +* [NeighborSearch tutorial (mlpack_knn / mlpack_kfn)](http://www.mlpack.org/doc/mlpack-git/doxygen/nstutorial.html) +* [LinearRegression tutorial (mlpack_linear_regression)](http://www.mlpack.org/doc/mlpack-git/doxygen/lrtutorial.html) +* [RangeSearch tutorial (mlpack_range_search)](http://www.mlpack.org/doc/mlpack-git/doxygen/rstutorial.html) +* [Density Estimation Trees tutorial (mlpack_det)](http://www.mlpack.org/doc/mlpack-git/doxygen/dettutorial.html) +* [K-Means tutorial (mlpack_kmeans)](http://www.mlpack.org/doc/mlpack-git/doxygen/kmtutorial.html) +* [FastMKS tutorial (mlpack_fastmks)](http://www.mlpack.org/doc/mlpack-git/doxygen/fmkstutorial.html) +* [Euclidean Minimum Spanning Trees tutorial (mlpack_emst)](http://www.mlpack.org/doc/mlpack-git/doxygen/emst_tutorial.html) +* [Alternating Matrix Factorization Tutorial](http://www.mlpack.org/doc/mlpack-git/doxygen/amftutorial.html) +* [Collaborative Filtering Tutorial](http://www.mlpack.org/doc/mlpack-git/doxygen/cftutorial.html) +* [Conventional Neural Evolution Tutorial](http://www.mlpack.org/doc/mlpack-git/doxygen/cnetutorial.html) ### Policy Class Documentation mlpack uses templates to achieve its genericity and flexibility. Some of the template types used by mlpack are common across multiple machine learning algorithms. The links below provide documentation for some of these common types. -* [The MetricType policy in mlpack](http://www.mlpack.org/docs/mlpack-git/doxygen/metrics.html) -* [The KernelType policy in mlpack](http://www.mlpack.org/docs/mlpack-git/doxygen/kernels.html) -* [The TreeType policy in mlpack](http://www.mlpack.org/docs/mlpack-git/doxygen/trees.html) +* [The MetricType policy in mlpack](http://www.mlpack.org/doc/mlpack-git/doxygen/metrics.html) +* [The KernelType policy in mlpack](http://www.mlpack.org/doc/mlpack-git/doxygen/kernels.html) +* [The TreeType policy in mlpack](http://www.mlpack.org/doc/mlpack-git/doxygen/trees.html) diff --git a/src/mlpack/bindings/markdown/print_docs.cpp b/src/mlpack/bindings/markdown/print_docs.cpp index 2711a87894..101fa53bce 100644 --- a/src/mlpack/bindings/markdown/print_docs.cpp +++ b/src/mlpack/bindings/markdown/print_docs.cpp @@ -13,7 +13,7 @@ // Make sure that this is defined. #ifndef DOXYGEN_PREFIX -#define DOXYGEN_PREFIX "https://mlpack.org/docs/mlpack-git/doxygen/" +#define DOXYGEN_PREFIX "https://mlpack.org/doc/mlpack-git/doxygen/" #endif using namespace std;