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Diffstat (limited to 'docs/mllib-guide.md')
| -rw-r--r-- | docs/mllib-guide.md | 9 |
1 files changed, 4 insertions, 5 deletions
diff --git a/docs/mllib-guide.md b/docs/mllib-guide.md index a5e0cc5080..eff856104c 100644 --- a/docs/mllib-guide.md +++ b/docs/mllib-guide.md @@ -11,7 +11,7 @@ namely, binary classification, regression, clustering and collaborative filtering, as well as an underlying gradient descent optimization primitive. # Available Methods -The following links provide a detailed explanation of the methods and usage examples for each of them: +The following links provide a detailed explanation of the methods and usage examples for each of them: * <a href="mllib-classification-regression.html">Classification and Regression</a> * Binary Classification @@ -33,10 +33,9 @@ The following links provide a detailed explanation of the methods and usage exam # Dependencies MLlib uses the [jblas](https://github.com/mikiobraun/jblas) linear algebra library, which itself -depends on native Fortran routines. You may need to install the +depends on native Fortran routines. You may need to install the [gfortran runtime library](https://github.com/mikiobraun/jblas/wiki/Missing-Libraries) -if it is not already present on your nodes. MLlib will throw a linking error if it cannot +if it is not already present on your nodes. MLlib will throw a linking error if it cannot detect these libraries automatically. -To use MLlib in Python, you will need [NumPy](http://www.numpy.org) version 1.7 or newer. - +To use MLlib in Python, you will need [NumPy](http://www.numpy.org) version 1.4 or newer. |