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Diffstat (limited to 'site/mllib/index.html')
| -rw-r--r-- | site/mllib/index.html | 30 |
1 files changed, 16 insertions, 14 deletions
diff --git a/site/mllib/index.html b/site/mllib/index.html index 4ac0dde7a..6cbedbe8a 100644 --- a/site/mllib/index.html +++ b/site/mllib/index.html @@ -104,7 +104,7 @@ </a> <ul class="dropdown-menu"> <li><a href="/documentation.html">Overview</a></li> - <li><a href="/docs/latest/">Latest Release (Spark 1.0.2)</a></li> + <li><a href="/docs/latest/">Latest Release (Spark 1.1.0)</a></li> <li><a href="/examples.html">Examples</a></li> </ul> </li> @@ -132,6 +132,9 @@ <h5>Latest News</h5> <ul class="list-unstyled"> + <li><a href="/news/spark-1-1-0-released.html">Spark 1.1.0 released</a> + <span class="small">(Sep 11, 2014)</span></li> + <li><a href="/news/spark-1-0-2-released.html">Spark 1.0.2 released</a> <span class="small">(Aug 05, 2014)</span></li> @@ -141,9 +144,6 @@ <li><a href="/news/spark-summit-2014-videos-posted.html">Spark Summit 2014 videos posted</a> <span class="small">(Jul 18, 2014)</span></li> - <li><a href="/news/spark-1-0-1-released.html">Spark 1.0.1 released</a> - <span class="small">(Jul 11, 2014)</span></li> - </ul> <p class="small" style="text-align: right;"><a href="/news/index.html">Archive</a></p> </div> @@ -191,9 +191,9 @@ points = spark.textFile(<span class="string">"hdfs://..."</span>)<br /> .<span class="sparkop">map</span>(<span class="closure">parsePoint</span>)<br /> <br /> - model = KMeans.<span class="sparkop">train</span>(points) + model = KMeans.<span class="sparkop">train</span>(points, k=10) </div> - <div class="caption">Calling MLlib in Scala</div> + <div class="caption">Calling MLlib in Python</div> </div> </div> </div> @@ -247,16 +247,18 @@ <div class="col-md-4 col-padded"> <h3>Algorithms</h3> <p> - MLlib 0.9 contains the following algorithms: + MLlib 1.1 contains the following algorithms: </p> <ul class="list-narrow"> - <li>K-means clustering with <a href="http://theory.stanford.edu/~sergei/papers/vldb12-kmpar.pdf">K-means|| initialization</a>.</li> - <li>L<sub>1</sub>- and L<sub>2</sub>-regularized <a href="http://en.wikipedia.org/wiki/Linear_regression">linear regression</a>.</li> - <li>L<sub>1</sub>- and L<sub>2</sub>-regularized <a href="http://en.wikipedia.org/wiki/Logistic_regression">logistic regression</a>.</li> - <li><a href="http://www.hpl.hp.com/personal/Robert_Schreiber/papers/2008%20AAIM%20Netflix/netflix_aaim08(submitted).pdf">Alternating least squares</a> collaborative filtering, with explicit - ratings or <a href="http://www2.research.att.com/~yifanhu/PUB/cf.pdf">implicit feedback</a>.</li> - <li><a href="http://en.wikipedia.org/wiki/Naive_Bayes_classifier">Naive Bayes</a> multinomial classification.</li> - <li>Stochastic gradient descent.</li> + <li>linear SVM and logistic regression</li> + <li>classification and regression tree</li> + <li>k-means clustering</li> + <li>recommendation via alternating least squares</li> + <li>singular value decomposition</li> + <li>linear regression with L<sub>1</sub>- and L<sub>2</sub>-regularization</li> + <li>multinomial naive Bayes</li> + <li>basic statistics</li> + <li>feature transformations</li> </ul> <p>Refer to the <a href="/docs/latest/mllib-guide.html">MLlib guide</a> for usage examples.</p> </div> |