Fix issues that Shikhar pointed out.
This commit is contained in:
Ryan Curtin
@@ -31,7 +31,7 @@ build and install mlpack. You can copy-paste the commands into your shell.
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@code{.sh}
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sudo apt-get install libboost-all-dev g++ cmake libarmadillo-dev python-pip wget
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sudo pip install cython setuptools distutils numpy pandas
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wget http://www.mlpack.org/files/mlpack-3.0.4.tar.gz
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wget https://www.mlpack.org/files/mlpack-3.0.4.tar.gz
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tar -xvzpf mlpack-3.0.4.tar.gz
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mkdir -p mlpack-3.0.4/build/ && cd mlpack-3.0.4/build/
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cmake ../ && make -j4 && sudo make install
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@@ -114,31 +114,20 @@ different mlpack learners, or to interface with other machine learning toolkits.
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@section python_quickstart_whatelse What else does mlpack implement?
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The example above has only shown a little bit of the functionality of mlpack.
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Lots of other commands are available with different functionality. Below is a
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list of all the mlpack functionality offered through Python, split into some
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categories.
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Lots of other commands are available with different functionality. A full list
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of each of these commands and full documentation can be found on the following
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page:
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- Classification techniques: <tt><a
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href="http://www.mlpack.org/doc/mlpack-git/python/adaboost.html">adaboost()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/decision_stump.html">decision_stump()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/decision_tree.html">decision_tree()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/hmm_train.html">hmm_train()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/hmm_generate.html">hmm_generate()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/hmm_loglik.html">hmm_loglik()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/hmm_viterbi.html">hmm_viterbi()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/hoeffding_tree.html">hoeffding_tree()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/logistic_regression.html">logistic_regression()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/nbc.html">nbc()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/perceptron.html">perceptron()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/random_forest.html">random_forest()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/softmax_regression.html">softmax_regression()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/cf.html">cf()</a></tt>
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- <a href="https://www.mlpack.org/doc/mlpack-git/python_documentation.html">Python documentation</a>
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- Distance-based problems: <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/approx_kfn.html">approx_kfn()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/emst.html">emst()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/fastmks.html">fastmks()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/kfn.html">kfn()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/knn.html">knn()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/krann.html">krann()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/lsh.html">lsh()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/det.html">det()</a></tt>
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- Clustering: <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/kmeans.html">kmeans()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/mean_shift.html">mean_shift()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/gmm_train.html">gmm_train()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/gmm_generate.html">gmm_generate()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/gmm_probability.html">gmm_probability()</a></tt>
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- Transformations: <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/pca.html">pca()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/radical.html">radical()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/local_coordinate_coding.html">local_coordinate_coding()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/sparse_coding.html">sparse_coding()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/nca.html">nca()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/kernel_pca.html">kernel_pca()</a></tt>
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- Regression: <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/linear_regression.html">linear_regression()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/lars.html">lars()</a></tt>
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- Preprocessing/other: <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/preprocess_binarize.html">preprocess_binarize()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/preprocess_split.html">preprocess_split()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/preprocess_describe.html">preprocess_describe()</a></tt>, <tt><a href="http://www.mlpack.org/doc/mlpack-git/python/nmf.html">nmf()</a></tt>
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For more information on what mlpack does, see http://www.mlpack.org/about.html.
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For more information on what mlpack does, see https://www.mlpack.org/about.html.
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Next, let's go through another example for providing movie recommendations with
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mlpack.
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@section python_quickstart_movierecs Using mlpack for movie recommendations
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In this example, we'll train a collaborative filtering model using mlpack's
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<tt><a href="http://www.mlpack.org/doc/mlpack-git/python/cf.html">cf()</a></tt> method. We'll train this on the MovieLens dataset from
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<tt><a href="https://www.mlpack.org/doc/mlpack-git/python_documentation.html#cf">cf()</a></tt> method. We'll train this on the MovieLens dataset from
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https://grouplens.org/datasets/movielens/, and then we'll use the model that we
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train to give recommendations.
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@@ -204,7 +193,7 @@ Now that you have done some simple work with mlpack, you have seen how it can
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easily plug into a data science workflow in Python. A great thing to do next
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would be to look at more documentation for the Python mlpack bindings:
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- <a href="http://www.mlpack.org/doc/mlpack-git/python_documentation.html">Python mlpack
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- <a href="https://www.mlpack.org/doc/mlpack-git/python_documentation.html">Python mlpack
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binding documentation</a>
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Also, mlpack is much more flexible from C++ and allows much greater
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@@ -212,13 +201,13 @@ functionality. So, more complicated tasks are possible if you are willing to
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write C++ (or perhaps Cython). To get started learning about mlpack in C++, the
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following resources might be helpful:
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- <a href="http://www.mlpack.org/doc/mlpack-git/doxygen/tutorials.html">mlpack
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- <a href="https://www.mlpack.org/doc/mlpack-git/doxygen/tutorials.html">mlpack
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C++ tutorials</a>
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- <a href="http://www.mlpack.org/doc/mlpack-git/doxygen/build.html">mlpack
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- <a href="https://www.mlpack.org/doc/mlpack-git/doxygen/build.html">mlpack
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build and installation guide</a>
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- <a href="http://www.mlpack.org/doc/mlpack-git/doxygen/sample.html">Simple
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- <a href="https://www.mlpack.org/doc/mlpack-git/doxygen/sample.html">Simple
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sample C++ mlpack programs</a>
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- <a href="http://www.mlpack.org/doc/mlpack-git/doxygen/index.html">mlpack
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- <a href="https://www.mlpack.org/doc/mlpack-git/doxygen/index.html">mlpack
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Doxygen documentation homepage</a>
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*/
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