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}); </script> </div> @@ -2500,7 +2500,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda - <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/3.1.1/anchor.min.js";></script> + <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.0/anchor.min.js";></script> http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/9d62b788/userguide/binaryclass/news20_rf.html ---------------------------------------------------------------------- diff --git a/userguide/binaryclass/news20_rf.html b/userguide/binaryclass/news20_rf.html index 8d5b3a4..d328203 100644 --- a/userguide/binaryclass/news20_rf.html +++ b/userguide/binaryclass/news20_rf.html @@ -2216,7 +2216,7 @@ under the License. --> <p>Hivemall Random Forest supports libsvm-like sparse inputs. </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>This feature, i.e., Sparse input support in Random Forest, is supported since Hivemall v0.5-rc.1 or later._ +<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>This feature, i.e., Sparse input support in Random Forest, is supported since Hivemall v0.5.0 or later._ <a href="http://hivemall.incubator.apache.org/userguide/ft_engineering/hashing.html#featurehashing-function"; target="_blank"><code>feature_hashing</code></a> function is useful to prepare feature vectors for Random Forest.</p></div></div> <!-- toc --><div id="toc" class="toc"> @@ -2242,7 +2242,7 @@ </code></pre> <div class="panel panel-warning"><div class="panel-heading"><h3 class="panel-title" id="caution"><i class="fa fa-exclamation-triangle"></i> Caution</h3></div><div class="panel-body"><p>label must be in <code>[0, k)</code> where <code>k</code> is the number of classes.</p></div></div> <h2 id="prediction">Prediction</h2> -<pre><code class="lang-sql"><span class="hljs-keyword">SET</span> hivevar:classification=<span class="hljs-literal">true</span>; +<pre><code class="lang-sql"><span class="hljs-comment">-- SET hivevar:classification=true;</span> <span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> rf_predicted; <span class="hljs-keyword">create</span> <span class="hljs-keyword">table</span> rf_predicted @@ -2255,7 +2255,10 @@ <span class="hljs-keyword">SELECT</span> <span class="hljs-keyword">rowid</span>, m.model_weight, - tree_predict(m.model_id, m.<span class="hljs-keyword">model</span>, t.features, ${classification}) <span class="hljs-keyword">as</span> predicted + <span class="hljs-comment">-- v0.5.0 and later</span> + tree_predict(m.model_id, m.<span class="hljs-keyword">model</span>, t.features, <span class="hljs-string">"-classification"</span>) <span class="hljs-keyword">as</span> predicted + <span class="hljs-comment">-- before v0.5.0</span> + <span class="hljs-comment">-- tree_predict(m.model_id, m.model, t.features, ${classification}) as predicted</span> <span class="hljs-keyword">FROM</span> rf_model m <span class="hljs-keyword">LEFT</span> <span class="hljs-keyword">OUTER</span> <span class="hljs-keyword">JOIN</span> <span class="hljs-comment">-- CROSS JOIN</span> @@ -2336,7 +2339,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda <script> var gitbook = gitbook || []; 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}); </script> </div> @@ -2559,7 +2559,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda - <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/3.1.1/anchor.min.js";></script> + <script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/4.1.0/anchor.min.js";></script> http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/9d62b788/userguide/binaryclass/titanic_rf.html ---------------------------------------------------------------------- diff --git a/userguide/binaryclass/titanic_rf.html b/userguide/binaryclass/titanic_rf.html index 87a2bb8..f7016a2 100644 --- a/userguide/binaryclass/titanic_rf.html +++ b/userguide/binaryclass/titanic_rf.html @@ -2344,8 +2344,8 @@ awk <span class="hljs-string">'{ FPAT="([^,]*)|(\"[^\"]+\&qu <p>Q,C,C,Q,Q,Q,C,Q,C,C</p> </blockquote> <p><code>Q</code> and <code>C</code> represent quantitative variable and categorical variables, respectively.</p> -<p><em>Caution:</em> Note that the output of <code>guess_attribute_types</code> is not perfect. Revise it by your self. -For example, <code>pclass</code> is a categorical variable.</p> +<div class="panel panel-warning"><div class="panel-heading"><h3 class="panel-title" id="caution"><i class="fa fa-exclamation-triangle"></i> Caution</h3></div><div class="panel-body"><p>Note that the output of <code>guess_attribute_types</code> is not perfect. Revise it by your self. +For example, <code>pclass</code> is a categorical variable.</p></div></div> <pre><code class="lang-sql"><span class="hljs-keyword">set</span> hivevar:attrs=C,C,C,Q,Q,Q,C,Q,C,C; <span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> model_rf; @@ -2353,7 +2353,6 @@ For example, <code>pclass</code> is a categorical variable.</p> <span class="hljs-keyword">AS</span> <span class="hljs-keyword">select</span> train_randomforest_classifier(features, survived, <span class="hljs-string">"-trees 500 -attrs ${attrs}"</span>) - <span class="hljs-comment">-- as (model_id, model_type, pred_model, var_importance, oob_errors, oob_tests)</span> <span class="hljs-keyword">from</span> train_rf ; @@ -2368,7 +2367,7 @@ For example, <code>pclass</code> is a categorical variable.</p> <p>[137.00242639169272,1194.2140119834373,328.78017188176966,628.2568660509628,200.31275032394072,160.12876797647078,1083.5987543408116,664.1234312561456,422.89449844090393,130.72019667694784] 0.18742985409652077</p> </blockquote> <h1 id="prediction">Prediction</h1> -<pre><code class="lang-sql"><span class="hljs-keyword">SET</span> hivevar:classification=<span class="hljs-literal">true</span>; +<pre><code class="lang-sql"><span class="hljs-comment">-- SET hivevar:classification=true;</span> <span class="hljs-keyword">set</span> hive.<span class="hljs-keyword">auto</span>.<span class="hljs-keyword">convert</span>.<span class="hljs-keyword">join</span>=<span class="hljs-literal">true</span>; <span class="hljs-keyword">SET</span> hive.mapjoin.optimized.hashtable=<span class="hljs-literal">false</span>; <span class="hljs-keyword">SET</span> mapred.reduce.tasks=<span class="hljs-number">16</span>; @@ -2385,23 +2384,23 @@ For example, <code>pclass</code> is a categorical variable.</p> <span class="hljs-keyword">SELECT</span> passengerid, <span class="hljs-comment">-- rf_ensemble(predicted) as predicted</span> - <span class="hljs-comment">-- hivemall v0.5-rc.1 or later</span> + <span class="hljs-comment">-- v0.5.0 or later</span> rf_ensemble(predicted.<span class="hljs-keyword">value</span>, predicted.posteriori, model_weight) <span class="hljs-keyword">as</span> predicted <span class="hljs-comment">-- rf_ensemble(predicted.value, predicted.posteriori) as predicted -- avoid OOB accuracy (i.e., model_weight)</span> <span class="hljs-keyword">FROM</span> ( <span class="hljs-keyword">SELECT</span> t.passengerid, - <span class="hljs-comment">-- hivemall v0.4.1-alpha.3 or later</span> + <span class="hljs-comment">-- from v0.4.1-alpha.3 to v0.4.2-rc4</span> <span class="hljs-comment">-- tree_predict(p.model_id, p.model_type, p.pred_model, t.features, ${classification}) as predicted</span> - <span class="hljs-comment">-- hivemall v0.5-rc.1 or later</span> + <span class="hljs-comment">-- v0.5.0 or later</span> p.model_weight, - tree_predict(p.model_id, p.<span class="hljs-keyword">model</span>, t.features, ${classification}) <span class="hljs-keyword">as</span> predicted - <span class="hljs-comment">-- tree_predict_v1(p.model_id, p.model_type, p.pred_model, t.features, ${classification}) as predicted -- to use the old model in v0.5-rc.1 or later</span> + tree_predict(p.model_id, p.<span class="hljs-keyword">model</span>, t.features, <span class="hljs-string">"-classification"</span>) <span class="hljs-keyword">as</span> predicted + <span class="hljs-comment">-- tree_predict_v1(p.model_id, p.model_type, p.pred_model, t.features, ${classification}) as predicted -- to use the old model in v0.5.0 or later</span> <span class="hljs-keyword">FROM</span> ( <span class="hljs-keyword">SELECT</span> - <span class="hljs-comment">-- hivemall v0.4.1-alpha.3 or later</span> + <span class="hljs-comment">-- from v0.4.1-alpha.3 or v0.4.2-rc4</span> <span class="hljs-comment">-- model_id, model_type, pred_model</span> - <span class="hljs-comment">-- hivemall v0.5-rc.1 or later</span> + <span class="hljs-comment">-- v0.5.0 or later</span> model_id, model_weight, <span class="hljs-keyword">model</span> <span class="hljs-keyword">FROM</span> model_rf @@ -2414,7 +2413,7 @@ For example, <code>pclass</code> is a categorical variable.</p> ) t2 ; </code></pre> -<div class="panel panel-warning"><div class="panel-heading"><h3 class="panel-title" id="caution"><i class="fa fa-exclamation-triangle"></i> Caution</h3></div><div class="panel-body"><p><code>tree_predict_v1</code> is for the backward compatibility for using prediction models built before <code>v0.5-rc.1</code> on <code>v0.5-rc.1</code> or later.</p></div></div> +<div class="panel panel-warning"><div class="panel-heading"><h3 class="panel-title" id="caution"><i class="fa fa-exclamation-triangle"></i> Caution</h3></div><div class="panel-body"><p><code>tree_predict_v1</code> is for the backward compatibility for using prediction models built before <code>v0.5.0</code> on <code>v0.5.0</code> or later.</p></div></div> <h1 id="kaggle-submission">Kaggle submission</h1> <pre><code class="lang-sql"><span class="hljs-keyword">drop</span> <span class="hljs-keyword">table</span> predicted_rf_submit; <span class="hljs-keyword">create</span> <span class="hljs-keyword">table</span> predicted_rf_submit @@ -2432,7 +2431,7 @@ sed -i <span class="hljs-_">-e</span> <span class="hljs-string">"1i Passeng </code></pre> <p>Accuracy would gives <code>0.76555</code> for a Kaggle submission.</p> <h1 id="graphvis-export">Graphvis export</h1> -<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><code>tree_export</code> feature is supported from Hivemall v0.5-rc.1 or later. +<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><code>tree_export</code> feature is supported from Hivemall v0.5.0 or later. Better to limit tree depth on training by <code>-depth</code> option to plot a Decision Tree.</p></div></div> <p>Hivemall provide <code>tree_export</code> to export a decision tree into <a href="http://www.graphviz.org/"; target="_blank">Graphviz</a> or human-readable Javascript format. You can find the usage by issuing the following query:</p> <pre><code>> select tree_export("","-help"); @@ -2490,7 +2489,7 @@ usage: tree_export(string model, const string options, optional <blockquote> <p>[116.12055542977338,960.8569891444097,291.08765260103837,469.74671636586226,163.721292772701,120.784769882858,847.9769298113661,554.4617571355476,346.3500941757221,97.42593940113392] 0.1838351822503962</p> </blockquote> -<pre><code class="lang-sql"><span class="hljs-keyword">SET</span> hivevar:classification=<span class="hljs-literal">true</span>; +<pre><code class="lang-sql"><span class="hljs-comment">-- SET hivevar:classification=true;</span> <span class="hljs-keyword">SET</span> hive.mapjoin.optimized.hashtable=<span class="hljs-literal">false</span>; <span class="hljs-keyword">SET</span> mapred.reduce.tasks=<span class="hljs-number">16</span>; @@ -2506,23 +2505,24 @@ usage: tree_export(string model, const string options, optional <span class="hljs-keyword">SELECT</span> passengerid, <span class="hljs-comment">-- rf_ensemble(predicted) as predicted</span> - <span class="hljs-comment">-- hivemall v0.5-rc.1 or later</span> + <span class="hljs-comment">-- v0.5.0 or later</span> rf_ensemble(predicted.<span class="hljs-keyword">value</span>, predicted.posteriori, model_weight) <span class="hljs-keyword">as</span> predicted <span class="hljs-comment">-- rf_ensemble(predicted.value, predicted.posteriori) as predicted -- avoid OOB accuracy (i.e., model_weight)</span> <span class="hljs-keyword">FROM</span> ( <span class="hljs-keyword">SELECT</span> t.passengerid, - <span class="hljs-comment">-- hivemall v0.4.1-alpha.3 or later</span> + <span class="hljs-comment">-- from v0.4.1-alpha.3 or v0.4.2-rc4</span> <span class="hljs-comment">-- tree_predict(p.model_id, p.model_type, p.pred_model, t.features, ${classification}) as predicted</span> - <span class="hljs-comment">-- hivemall v0.5-rc.1 or later</span> + <span class="hljs-comment">-- v0.5.0 or later</span> p.model_weight, - tree_predict(p.model_id, p.<span class="hljs-keyword">model</span>, t.features, ${classification}) <span class="hljs-keyword">as</span> predicted - <span class="hljs-comment">-- tree_predict_v1(p.model_id, p.model_type, p.pred_model, t.features, ${classification}) as predicted -- to use the old model in v0.5-rc.1 or later</span> + tree_predict(p.model_id, p.<span class="hljs-keyword">model</span>, t.features, <span class="hljs-string">"-classification"</span>) <span class="hljs-keyword">as</span> predicted + <span class="hljs-comment">-- tree_predict(p.model_id, p.model, t.features, ${classification}) as predicted</span> + <span class="hljs-comment">-- tree_predict_v1(p.model_id, p.model_type, p.pred_model, t.features, ${classification}) as predicted -- to use the old model in v0.5.0 or later</span> <span class="hljs-keyword">FROM</span> ( <span class="hljs-keyword">SELECT</span> - <span class="hljs-comment">-- hivemall v0.4.1-alpha.3 or later</span> + <span class="hljs-comment">-- from v0.4.1-alpha.3 to v0.4.2-rc4</span> <span class="hljs-comment">-- model_id, model_type, pred_model</span> - <span class="hljs-comment">-- hivemall v0.5-rc.1 or later</span> + <span class="hljs-comment">-- v0.5.0 or later</span> model_id, model_weight, <span class="hljs-keyword">model</span> <span class="hljs-keyword">FROM</span> model_rf_07 @@ -2613,7 +2613,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda <script> var gitbook = gitbook || []; 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