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Posted to commits@hivemall.apache.org by my...@apache.org on 2017/05/09 08:31:37 UTC
[1/9] incubator-hivemall-site git commit: Fixed pLSA documentation
Repository: incubator-hivemall-site
Updated Branches:
refs/heads/asf-site 15b9991a5 -> d20191813
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d2019181/userguide/tips/index.html
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index adf3cbc..b8629b4 100644
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http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d2019181/userguide/tips/mixserver.html
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http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d2019181/userguide/tips/rand_amplify.html
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[2/9] incubator-hivemall-site git commit: Fixed pLSA documentation
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d2019181/userguide/spark/binaryclass/a9a_df.html
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[8/9] incubator-hivemall-site git commit: Fixed pLSA documentation
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d2019181/userguide/binaryclass/kdd2010b_dataset.html
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@@ -2116,7 +2116,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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diff --git a/userguide/binaryclass/webspam.html b/userguide/binaryclass/webspam.html
index 604457f..0abb359 100644
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diff --git a/userguide/binaryclass/webspam_dataset.html b/userguide/binaryclass/webspam_dataset.html
index ca3fd39..dc93275 100644
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diff --git a/userguide/binaryclass/webspam_scw.html b/userguide/binaryclass/webspam_scw.html
index 3325c1c..7f547d7 100644
--- a/userguide/binaryclass/webspam_scw.html
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http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d2019181/userguide/clustering/lda.html
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diff --git a/userguide/clustering/lda.html b/userguide/clustering/lda.html
index e12404a..c9af401 100644
--- a/userguide/clustering/lda.html
+++ b/userguide/clustering/lda.html
@@ -2095,7 +2095,7 @@
docid, word
)
<span class="hljs-keyword">select</span>
- train_lda(feature, <span class="hljs-string">"-topic 2 -iter 20"</span>) <span class="hljs-keyword">as</span> (label, word, lambda)
+ train_lda(feature, <span class="hljs-string">"-topics 2 -iter 20"</span>) <span class="hljs-keyword">as</span> (label, word, lambda)
<span class="hljs-keyword">from</span> (
<span class="hljs-keyword">select</span> docid, collect_set(word_count) <span class="hljs-keyword">as</span> feature
<span class="hljs-keyword">from</span> word_counts
@@ -2104,7 +2104,7 @@
) t
;
</code></pre>
-<p>Here, an option <code>-topic 2</code> specifies the number of topics we assume in the set of documents.</p>
+<p>Here, an option <code>-topics 2</code> specifies the number of topics we assume in the set of documents.</p>
<p>Notice that <code>order by docid</code> ensures building a LDA model precisely in a single node. In case that you like to launch <code>train_lda</code> in parallel, following query hopefully returns similar (but might be slightly approximated) result:</p>
<pre><code class="lang-sql">with word_counts as (
<span class="hljs-comment">-- same as above</span>
@@ -2113,7 +2113,7 @@
label, word, <span class="hljs-keyword">avg</span>(lambda) <span class="hljs-keyword">as</span> lambda
<span class="hljs-keyword">from</span> (
<span class="hljs-keyword">select</span>
- train_lda(feature, <span class="hljs-string">"-topic 2 -iter 20"</span>) <span class="hljs-keyword">as</span> (label, word, lambda)
+ train_lda(feature, <span class="hljs-string">"-topics 2 -iter 20"</span>) <span class="hljs-keyword">as</span> (label, word, lambda)
<span class="hljs-keyword">from</span> (
<span class="hljs-keyword">select</span> docid, collect_set(f) <span class="hljs-keyword">as</span> feature
<span class="hljs-keyword">from</span> word_counts
@@ -2244,7 +2244,7 @@
)
<span class="hljs-keyword">select</span>
t.docid,
- lda_predict(t.word, t.<span class="hljs-keyword">value</span>, m.label, m.lambda, <span class="hljs-string">"-topic 2"</span>) <span class="hljs-keyword">as</span> probabilities
+ lda_predict(t.word, t.<span class="hljs-keyword">value</span>, m.label, m.lambda, <span class="hljs-string">"-topics 2"</span>) <span class="hljs-keyword">as</span> probabilities
<span class="hljs-keyword">from</span>
<span class="hljs-keyword">test</span> t
<span class="hljs-keyword">JOIN</span> lda_model m <span class="hljs-keyword">ON</span> (t.word = m.word)
@@ -2270,7 +2270,7 @@
</tr>
</tbody>
</table>
-<p>Importantly, an option <code>-topic</code> should be set to the same value as you set for training.</p>
+<p>Importantly, an option <code>-topics</code> is expected to be the same value as you set for training.</p>
<p>Since the probabilities are sorted in descending order, a label of the most promising topic is easily obtained as:</p>
<pre><code class="lang-sql"><span class="hljs-keyword">select</span> docid, probabilities[<span class="hljs-number">0</span>].label
<span class="hljs-keyword">from</span> topic
@@ -2350,7 +2350,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d2019181/userguide/clustering/plsa.html
----------------------------------------------------------------------
diff --git a/userguide/clustering/plsa.html b/userguide/clustering/plsa.html
index bf9c7a7..2cc49c5 100644
--- a/userguide/clustering/plsa.html
+++ b/userguide/clustering/plsa.html
@@ -2238,7 +2238,13 @@ topic <span class="hljs-keyword">as</span> (
</code></pre>
<p>This value controls <strong>how much iterative model update is affected by the old results</strong>.</p>
<p>From an algorithmic point of view, training pLSA (and LDA) iteratively repeats certain operations and updates the target value (i.e., probability obtained as a result of <code>train_plsa()</code>). This iterative procedure gradually makes the probabilities more accurate. What <code>alpha</code> does is to control the degree of the change of probabilities in each step.</p>
-<p>Normally, <code>alpha</code> is set to a small value from 0.0 to 0.5 (default is 0.5).
+<p>Importantly, pLSA is likely to overfit single mini-batch. As a result, <span class="katex"><span class="katex-mathml"><math><semantics><mrow><mi>P</mi><mo>(</mo><mi>w</mi><mi mathvariant="normal">∣</mi><mi>z</mi><mo>)</mo></mrow><annotation encoding="application/x-tex">P(w|z)</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="strut" style="height:0.75em;"></span><span class="strut bottom" style="height:1em;vertical-align:-0.25em;"></span><span class="base textstyle uncramped"><span class="mord mathit" style="margin-right:0.13889em;">P</span><span class="mopen">(</span><span class="mord mathit" style="margin-right:0.02691em;">w</span><span class="mord mathrm">∣</span><span class="mord mathit" style="margin-right:0.04398em;">z</span><span class="mclose">)</span></span></span></span> could be particularly bad values (i.e., <span class="katex"><span class="katex-mathml"><math><semantics><mrow><mo>(</mo><mi>w</mi><mi mathvarian
t="normal">∣</mi><mi>z</mi><mo>)</mo><mo>=</mo><mn>0</mn></mrow><annotation encoding="application/x-tex">(w|z) = 0</annotation></semantics></math></span><span class="katex-html" aria-hidden="true"><span class="strut" style="height:0.75em;"></span><span class="strut bottom" style="height:1em;vertical-align:-0.25em;"></span><span class="base textstyle uncramped"><span class="mopen">(</span><span class="mord mathit" style="margin-right:0.02691em;">w</span><span class="mord mathrm">∣</span><span class="mord mathit" style="margin-right:0.04398em;">z</span><span class="mclose">)</span><span class="mrel">=</span><span class="mord mathrm">0</span></span></span></span>), and <code>train_plsa()</code> sometimes fails with an exception like:</p>
+<pre><code>Perplexity would be Infinity. Try different mini-batch size `-s`, larger `-delta` and/or larger `-alpha`.
+</code></pre><p>In that case, you need to try different hyper-parameters to avoid overfitting as the exception suggests.</p>
+<p>For instance, <a href="http://qwone.com/~jason/20Newsgroups/" target="_blank">20 newsgroups dataset</a> which consists of 10906 realistic documents empirically requires the following options:</p>
+<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><!--
Licensed to the Apache Software Foundation (ASF) under one
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@@ -2294,7 +2300,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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[3/9] incubator-hivemall-site git commit: Fixed pLSA documentation
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d2019181/userguide/search_index.json
----------------------------------------------------------------------
diff --git a/userguide/search_index.json b/userguide/search_index.json
index a8010f0..568b0df 100644
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[9/9] incubator-hivemall-site git commit: Fixed pLSA documentation
Posted by my...@apache.org.
Fixed pLSA documentation
Project: http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/commit/d2019181
Tree: http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/tree/d2019181
Diff: http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/diff/d2019181
Branch: refs/heads/asf-site
Commit: d20191813548624edde2f98630ee5557a61fc8a0
Parents: 15b9991
Author: myui <yu...@gmail.com>
Authored: Tue May 9 17:31:22 2017 +0900
Committer: myui <yu...@gmail.com>
Committed: Tue May 9 17:31:22 2017 +0900
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userguide/anomaly/changefinder.html | 2 +-
userguide/anomaly/lof.html | 2 +-
userguide/anomaly/sst.html | 2 +-
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userguide/binaryclass/news20.html | 2 +-
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userguide/multiclass/news20.html | 2 +-
userguide/multiclass/news20_dataset.html | 2 +-
userguide/multiclass/news20_ensemble.html | 2 +-
userguide/multiclass/news20_one-vs-the-rest.html | 2 +-
.../multiclass/news20_one-vs-the-rest_dataset.html | 2 +-
userguide/multiclass/news20_pa.html | 2 +-
userguide/multiclass/news20_scw.html | 2 +-
userguide/recommend/cf.html | 2 +-
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userguide/troubleshooting/oom.html | 2 +-
102 files changed, 114 insertions(+), 108 deletions(-)
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http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d2019181/userguide/anomaly/changefinder.html
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diff --git a/userguide/anomaly/changefinder.html b/userguide/anomaly/changefinder.html
index df18423..460f9a9 100644
--- a/userguide/anomaly/changefinder.html
+++ b/userguide/anomaly/changefinder.html
@@ -2253,7 +2253,7 @@ Apache Hivemall is an effort undergoing incubation at The Apache Software Founda
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[6/9] incubator-hivemall-site git commit: Fixed pLSA documentation
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d2019181/userguide/geospatial/latlon.html
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[5/9] incubator-hivemall-site git commit: Fixed pLSA documentation
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d2019181/userguide/multiclass/news20.html
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http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d2019181/userguide/multiclass/news20_dataset.html
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[4/9] incubator-hivemall-site git commit: Fixed pLSA documentation
Posted by my...@apache.org.
http://git-wip-us.apache.org/repos/asf/incubator-hivemall-site/blob/d2019181/userguide/recommend/movielens_mf.html
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[7/9] incubator-hivemall-site git commit: Fixed pLSA documentation
Posted by my...@apache.org.
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