Merge pull request #1098 from weixuanfu/issue_1088

Increase MAX_EVAL_SECS in pretest for dataset with large numbers of features

docs/index.html

@@ -204,5 +204,5 @@
 
 <!--
 MkDocs version : 1.1.2
-Build Date UTC : 2020-07-13 13:44:17.272181+00:00
+Build Date UTC : 2020-07-21 20:34:39.398221+00:00
 -->

docs/installing/index.html

@@ -161,7 +161,7 @@ <h1 id="installation">Installation</h1>
 <p><a href="https://joblib.readthedocs.io/en/latest/">joblib</a></p>
 </li>
 </ul>
-<p>Most of the necessary Python packages can be installed via the <a href="https://www.continuum.io/downloads">Anaconda Python distribution</a>, which we strongly recommend that you use. We also strongly recommend that you use of Python 3 over Python 2 if you're given the choice.</p>
+<p>Most of the necessary Python packages can be installed via the <a href="https://www.anaconda.com/products/individual">Anaconda Python distribution</a>, which we strongly recommend that you use. <strong>Support for Python 3.4 and below has been officially dropped since version 0.11.0.</strong></p>
 <p>You can install TPOT using <code>pip</code> or <code>conda-forge</code>.</p>
 <h2 id="pip">pip</h2>
 <p>NumPy, SciPy, scikit-learn, pandas, joblib, and PyTorch can be installed in Anaconda via the command:</p>

docs/sitemap.xml

@@ -1,43 +1,43 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9"><url>
      <loc>http://epistasislab.github.io/tpot/</loc>
-     <lastmod>2020-07-13</lastmod>
+     <lastmod>2020-07-21</lastmod>
      <changefreq>daily</changefreq>
     </url><url>
      <loc>http://epistasislab.github.io/tpot/installing/</loc>
-     <lastmod>2020-07-13</lastmod>
+     <lastmod>2020-07-21</lastmod>
      <changefreq>daily</changefreq>
     </url><url>
      <loc>http://epistasislab.github.io/tpot/using/</loc>
-     <lastmod>2020-07-13</lastmod>
+     <lastmod>2020-07-21</lastmod>
      <changefreq>daily</changefreq>
     </url><url>
      <loc>http://epistasislab.github.io/tpot/api/</loc>
-     <lastmod>2020-07-13</lastmod>
+     <lastmod>2020-07-21</lastmod>
      <changefreq>daily</changefreq>
     </url><url>
      <loc>http://epistasislab.github.io/tpot/examples/</loc>
-     <lastmod>2020-07-13</lastmod>
+     <lastmod>2020-07-21</lastmod>
      <changefreq>daily</changefreq>
     </url><url>
      <loc>http://epistasislab.github.io/tpot/contributing/</loc>
-     <lastmod>2020-07-13</lastmod>
+     <lastmod>2020-07-21</lastmod>
      <changefreq>daily</changefreq>
     </url><url>
      <loc>http://epistasislab.github.io/tpot/releases/</loc>
-     <lastmod>2020-07-13</lastmod>
+     <lastmod>2020-07-21</lastmod>
      <changefreq>daily</changefreq>
     </url><url>
      <loc>http://epistasislab.github.io/tpot/citing/</loc>
-     <lastmod>2020-07-13</lastmod>
+     <lastmod>2020-07-21</lastmod>
      <changefreq>daily</changefreq>
     </url><url>
      <loc>http://epistasislab.github.io/tpot/support/</loc>
-     <lastmod>2020-07-13</lastmod>
+     <lastmod>2020-07-21</lastmod>
      <changefreq>daily</changefreq>
     </url><url>
      <loc>http://epistasislab.github.io/tpot/related/</loc>
-     <lastmod>2020-07-13</lastmod>
+     <lastmod>2020-07-21</lastmod>
      <changefreq>daily</changefreq>
     </url>
 </urlset>

docs_sources/installing.md

@@ -20,7 +20,8 @@ TPOT is built on top of several existing Python libraries, including:
 
 * [joblib](https://joblib.readthedocs.io/en/latest/)
 
-Most of the necessary Python packages can be installed via the [Anaconda Python distribution](https://www.continuum.io/downloads), which we strongly recommend that you use. We also strongly recommend that you use of Python 3 over Python 2 if you're given the choice.
+Most of the necessary Python packages can be installed via the [Anaconda Python distribution](https://www.anaconda.com/products/individual), which we strongly recommend that you use. **Support for Python 3.4 and below has been officially dropped since version 0.11.0.**
+
 
 You can install TPOT using `pip` or `conda-forge`.
 

tpot/decorators.py

@@ -33,7 +33,7 @@
 
 
 NUM_TESTS = 10
-MAX_EVAL_SECS = 2
+MAX_EVAL_SECS = 10
 
 
 def _pre_test(func):