http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/ad3e27db/userguide/clustering/plsa.html ---------------------------------------------------------------------- diff --git a/userguide/clustering/plsa.html b/userguide/clustering/plsa.html index 2cc49c5..a96146e 100644 --- a/userguide/clustering/plsa.html +++ b/userguide/clustering/plsa.html @@ -2245,7 +2245,7 @@ topic <span class="hljs-keyword">as</span> ( <pre><code class="lang-sql"><span class="hljs-keyword">SELECT</span> train_plsa(features, <span class="hljs-string">"-topics 20 -iter 10 -s 128 -delta 0.01 -alpha 512 -eps 0.1"</span>) </code></pre> <p>Clearly, <code>alpha</code> is much larger than <code>0.01</code> which was used for the dummy data above. Let you keep in mind that an appropriate value of <code>alpha</code> highly depends on the number of documents and mini-batch size. -<div id="page-footer"><hr><!-- +<div id="page-footer" class="localized-footer"><hr><!-- Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements. 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http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/ad3e27db/userguide/docker/getting_started.html ---------------------------------------------------------------------- diff --git a/userguide/docker/getting_started.html b/userguide/docker/getting_started.html index 52deb2b..a9e1925 100644 --- a/userguide/docker/getting_started.html +++ b/userguide/docker/getting_started.html @@ -2018,9 +2018,11 @@ <li><a href="#2-run-container">2. Run container</a><ul> <li><a href="#run-by-docker-compose">Run by docker-compose</a></li> <li><a href="#run-by-docker-command">Run by docker command</a></li> +<li><a href="#running-pre-built-docker-image-in-dockerhub">Running pre-built Docker image in Dockerhub</a></li> </ul> </li> <li><a href="#3-run-hivemall-on-docker">3. Run Hivemall on Docker</a><ul> +<li><a href="#accessing-hadoop-management-guis">Accessing Hadoop management GUIs</a></li> <li><a href="#load-data-into-hdfs-optional">Load data into HDFS (optional)</a></li> <li><a href="#build-hivemall-optional">Build Hivemall (optional)</a></li> </ul> @@ -2039,6 +2041,7 @@ <p> <code>docker-compose -f resources/docker/docker-compose.yml build</code></p> <h2 id="build-using-docker-command">Build using docker command</h2> <p> <code>docker build -f resources/docker/Dockerfile .</code></p> +<div class="panel panel-primary"><div class="panel-heading"><h3 class="panel-title" id="note"><i class="fa fa-edit"></i> Note</h3></div><div class="panel-body"><p>You can <a href="http://localhost:4000/docker/getting_started.html#running-pre-built-docker-image-in-dockerhub"; target="_blank">skip</a> building images by using existing Docker images.</p></div></div> <h1 id="2-run-container">2. Run container</h1> <h2 id="run-by-docker-compose">Run by docker-compose</h2> <ol> @@ -2051,18 +2054,32 @@ <li>Run <code>docker run -it ${docker_image_id}</code>. Refer <a href="https://docs.docker.com/engine/reference/run/"; target="_blank">Docker reference</a> for the command detail.</li> </ol> +<h2 id="running-pre-built-docker-image-in-dockerhub">Running pre-built Docker image in Dockerhub</h2> +<ol> +<li>Check <a href="https://hub.docker.com/r/hivemall/latest/tags/"; target="_blank">the latest tag</a> first.</li> +<li>Pull pre-build docker image from Dockerhub <code>docker pull hivemall/latest:20170517</code></li> +<li><code>docker run -p 8088:8088 -p 50070:50070 -p 19888:19888 -it hivemall/latest:20170517</code></li> +</ol> +<p>You can find pre-built Hivemall docker images in <a href="https://hub.docker.com/r/hivemall/latest/"; target="_blank">this repository</a>.</p> <h1 id="3-run-hivemall-on-docker">3. Run Hivemall on Docker</h1> <ol> <li>Type <code>hive</code> to run (<code>.hiverc</code> automatically loads Hivemall functions)</li> <li>Try your Hivemall queries!</li> </ol> +<h2 id="accessing-hadoop-management-guis">Accessing Hadoop management GUIs</h2> +<ul> +<li>YARN <a href="http://localhost:8088/"; target="_blank">http://localhost:8088/</a></li> +<li>HDFS <a href="http://localhost:50070/"; target="_blank">http://localhost:50070/</a></li> +<li>MR jobhistory server <a href="http://localhost:19888/"; target="_blank">http://localhost:19888/</a></li> +</ul> +<p>Note that you need to expose local ports e.g., by <code>-p 8088:8088 -p 50070:50070 -p 19888:19888</code> on running docker image.</p> <h2 id="load-data-into-hdfs-optional">Load data into HDFS (optional)</h2> <p> You can find an example script to load data into HDFS in <code>./bin/prepare_iris.sh</code>. The script loads iris dataset into <code>iris</code> database.</p> <h2 id="build-hivemall-optional">Build Hivemall (optional)</h2> <p> In the container, Hivemall resource is stored in <code>$HIVEMALL_PATH</code>. You can build Hivemall package by <code>cd $HIVEMALL_PATH && ./bin/build.sh</code>.</p> -<p><div id="page-footer"><hr><!-- +<p><div id="page-footer" class="localized-footer"><hr><!-- Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements. 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}); </script> </div> http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/ad3e27db/userguide/eval/auc.html ---------------------------------------------------------------------- diff --git a/userguide/eval/auc.html b/userguide/eval/auc.html index a8fcdfb..123ae29 100644 --- a/userguide/eval/auc.html +++ b/userguide/eval/auc.html @@ -2100,7 +2100,7 @@ <p>Hivemall has another metric called <a href="stat_eval.html#logarithmic-loss">Logarithmic Loss</a> for binary classification. Both AUC and Logarithmic Loss compute scores for probability-label pairs. </p> <p>Score produced by AUC is a relative metric based on sorted pairs. On the other hand, Logarithmic Loss simply gives a metric by comparing probability with its truth label one-by-one.</p> <p>To give an example, <code>auc(prob, label)</code> and <code>logloss(prob, label)</code> respectively returns <code>0.83333</code> and <code>0.54001</code> in the above case. Note that larger AUC and smaller Logarithmic Loss are better.</p> -<p><div id="page-footer"><hr><!-- +<p><div id="page-footer" class="localized-footer"><hr><!-- Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements. 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