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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN">
<html><head><title>Python: module main</title>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
</head><body bgcolor="#f0f0f8">
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="heading">
<tr bgcolor="#7799ee">
<td valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"> <br><big><big><strong>main</strong></big></big></font></td
><td align=right valign=bottom
><font color="#ffffff" face="helvetica, arial"><a href=".">index</a><br><a href="file:/home/mirasma/Main/Projects/Academics/RecSys/main.py">/home/mirasma/Main/Projects/Academics/RecSys/main.py</a></font></td></tr></table>
<p></p>
<p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#aa55cc">
<td colspan=3 valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"><big><strong>Modules</strong></big></font></td></tr>
<tr><td bgcolor="#aa55cc"><tt> </tt></td><td> </td>
<td width="100%"><table width="100%" summary="list"><tr><td width="25%" valign=top><a href="numpy.html">numpy</a><br>
</td><td width="25%" valign=top><a href="pandas.html">pandas</a><br>
</td><td width="25%" valign=top></td><td width="25%" valign=top></td></tr></table></td></tr></table><p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#ee77aa">
<td colspan=3 valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"><big><strong>Classes</strong></big></font></td></tr>
<tr><td bgcolor="#ee77aa"><tt> </tt></td><td> </td>
<td width="100%"><dl>
<dt><font face="helvetica, arial"><a href="builtins.html#object">builtins.object</a>
</font></dt><dd>
<dl>
<dt><font face="helvetica, arial"><a href="main.html#ColabrativeFiltering">ColabrativeFiltering</a>
</font></dt><dd>
<dl>
<dt><font face="helvetica, arial"><a href="main.html#CollaborativeWithBaseline">CollaborativeWithBaseline</a>
</font></dt></dl>
</dd>
</dl>
</dd>
</dl>
<p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#ffc8d8">
<td colspan=3 valign=bottom> <br>
<font color="#000000" face="helvetica, arial"><a name="ColabrativeFiltering">class <strong>ColabrativeFiltering</strong></a>(<a href="builtins.html#object">builtins.object</a>)</font></td></tr>
<tr bgcolor="#ffc8d8"><td rowspan=2><tt> </tt></td>
<td colspan=2><tt><a href="#ColabrativeFiltering">ColabrativeFiltering</a>(matrix, train, test, k=10)<br>
<br>
<br> </tt></td></tr>
<tr><td> </td>
<td width="100%">Methods defined here:<br>
<dl><dt><a name="ColabrativeFiltering-__init__"><strong>__init__</strong></a>(self, matrix, train, test, k=10)</dt><dd><tt>Initialize self. See help(type(self)) for accurate signature.</tt></dd></dl>
<dl><dt><a name="ColabrativeFiltering-get_rating"><strong>get_rating</strong></a>(self, userid, movieid)</dt><dd><tt>Get the rating for a user and movie<br>
<br>
Finds the average ratings among the top k users of 'userid' for the given 'movieid' <br>
Returns:<br>
rating (int)</tt></dd></dl>
<dl><dt><a name="ColabrativeFiltering-get_results"><strong>get_results</strong></a>(self)</dt><dd><tt>Calculate predicted ratings for train and test data</tt></dd></dl>
<dl><dt><a name="ColabrativeFiltering-get_top_k_users"><strong>get_top_k_users</strong></a>(self)</dt><dd><tt>Extract top k similar users for all users<br>
top_k_users (users * k) matrix: Contains indices of top k similar users in every row<br>
top_k_sim (users * k) matrix: The similarity value for each user with their top k similar users</tt></dd></dl>
<hr>
Data descriptors defined here:<br>
<dl><dt><strong>__dict__</strong></dt>
<dd><tt>dictionary for instance variables (if defined)</tt></dd>
</dl>
<dl><dt><strong>__weakref__</strong></dt>
<dd><tt>list of weak references to the object (if defined)</tt></dd>
</dl>
</td></tr></table> <p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#ffc8d8">
<td colspan=3 valign=bottom> <br>
<font color="#000000" face="helvetica, arial"><a name="CollaborativeWithBaseline">class <strong>CollaborativeWithBaseline</strong></a>(<a href="main.html#ColabrativeFiltering">ColabrativeFiltering</a>)</font></td></tr>
<tr bgcolor="#ffc8d8"><td rowspan=2><tt> </tt></td>
<td colspan=2><tt><a href="#CollaborativeWithBaseline">CollaborativeWithBaseline</a>(matrix, train, test, k=10)<br>
<br>
<br> </tt></td></tr>
<tr><td> </td>
<td width="100%"><dl><dt>Method resolution order:</dt>
<dd><a href="main.html#CollaborativeWithBaseline">CollaborativeWithBaseline</a></dd>
<dd><a href="main.html#ColabrativeFiltering">ColabrativeFiltering</a></dd>
<dd><a href="builtins.html#object">builtins.object</a></dd>
</dl>
<hr>
Methods defined here:<br>
<dl><dt><a name="CollaborativeWithBaseline-__init__"><strong>__init__</strong></a>(self, matrix, train, test, k=10)</dt><dd><tt>Initialize self. See help(type(self)) for accurate signature.</tt></dd></dl>
<dl><dt><a name="CollaborativeWithBaseline-find_global_mean"><strong>find_global_mean</strong></a>(self)</dt></dl>
<dl><dt><a name="CollaborativeWithBaseline-find_movie_deviation"><strong>find_movie_deviation</strong></a>(self)</dt></dl>
<dl><dt><a name="CollaborativeWithBaseline-find_user_deviation"><strong>find_user_deviation</strong></a>(self)</dt></dl>
<dl><dt><a name="CollaborativeWithBaseline-get_rating"><strong>get_rating</strong></a>(self, userid, movieid)</dt><dd><tt>Get the rating for a user and movie<br>
<br>
Finds the average ratings among the top k users of 'userid' for the given 'movieid' <br>
Returns:<br>
rating (int)</tt></dd></dl>
<hr>
Methods inherited from <a href="main.html#ColabrativeFiltering">ColabrativeFiltering</a>:<br>
<dl><dt><a name="CollaborativeWithBaseline-get_results"><strong>get_results</strong></a>(self)</dt><dd><tt>Calculate predicted ratings for train and test data</tt></dd></dl>
<dl><dt><a name="CollaborativeWithBaseline-get_top_k_users"><strong>get_top_k_users</strong></a>(self)</dt><dd><tt>Extract top k similar users for all users<br>
top_k_users (users * k) matrix: Contains indices of top k similar users in every row<br>
top_k_sim (users * k) matrix: The similarity value for each user with their top k similar users</tt></dd></dl>
<hr>
Data descriptors inherited from <a href="main.html#ColabrativeFiltering">ColabrativeFiltering</a>:<br>
<dl><dt><strong>__dict__</strong></dt>
<dd><tt>dictionary for instance variables (if defined)</tt></dd>
</dl>
<dl><dt><strong>__weakref__</strong></dt>
<dd><tt>list of weak references to the object (if defined)</tt></dd>
</dl>
</td></tr></table></td></tr></table><p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#eeaa77">
<td colspan=3 valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"><big><strong>Functions</strong></big></font></td></tr>
<tr><td bgcolor="#eeaa77"><tt> </tt></td><td> </td>
<td width="100%"><dl><dt><a name="-time"><strong>time</strong></a>(...)</dt><dd><tt><a href="#-time">time</a>() -> floating point number<br>
<br>
Return the current time in seconds since the Epoch.<br>
Fractions of a second may be present if the system clock provides them.</tt></dd></dl>
</td></tr></table>
</body></html>