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Performance Results.rtf
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Performance Results.rtf
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{\rtf1\adeflang1025\ansi\ansicpg1252\uc1\adeff31507\deff0\stshfdbch0\stshfloch31506\stshfhich31506\stshfbi31506\deflang1033\deflangfe1033\themelang1033\themelangfe0\themelangcs0{\fonttbl{\f0\fbidi \froman\fcharset0\fprq2{\*\panose 02020603050405020304}Times New Roman;}{\f2\fbidi \fmodern\fcharset0\fprq1{\*\panose 02070309020205020404}Courier New;}
{\f34\fbidi \froman\fcharset0\fprq2{\*\panose 02040503050406030204}Cambria Math;}{\flomajor\f31500\fbidi \froman\fcharset0\fprq2{\*\panose 02020603050405020304}Times New Roman;}
{\fdbmajor\f31501\fbidi \froman\fcharset0\fprq2{\*\panose 02020603050405020304}Times New Roman;}{\fhimajor\f31502\fbidi \froman\fcharset0\fprq2{\*\panose 02040503050406030204}Cambria;}
{\fbimajor\f31503\fbidi \froman\fcharset0\fprq2{\*\panose 02020603050405020304}Times New Roman;}{\flominor\f31504\fbidi \froman\fcharset0\fprq2{\*\panose 02020603050405020304}Times New Roman;}
{\fdbminor\f31505\fbidi \froman\fcharset0\fprq2{\*\panose 02020603050405020304}Times New Roman;}{\fhiminor\f31506\fbidi \fswiss\fcharset0\fprq2{\*\panose 020f0502020204030204}Calibri;}
{\fbiminor\f31507\fbidi \froman\fcharset0\fprq2{\*\panose 02020603050405020304}Times New Roman;}{\f39\fbidi \froman\fcharset238\fprq2 Times New Roman CE;}{\f40\fbidi \froman\fcharset204\fprq2 Times New Roman Cyr;}
{\f42\fbidi \froman\fcharset161\fprq2 Times New Roman Greek;}{\f43\fbidi \froman\fcharset162\fprq2 Times New Roman Tur;}{\f44\fbidi \froman\fcharset177\fprq2 Times New Roman (Hebrew);}{\f45\fbidi \froman\fcharset178\fprq2 Times New Roman (Arabic);}
{\f46\fbidi \froman\fcharset186\fprq2 Times New Roman Baltic;}{\f47\fbidi \froman\fcharset163\fprq2 Times New Roman (Vietnamese);}{\f59\fbidi \fmodern\fcharset238\fprq1 Courier New CE;}{\f60\fbidi \fmodern\fcharset204\fprq1 Courier New Cyr;}
{\f62\fbidi \fmodern\fcharset161\fprq1 Courier New Greek;}{\f63\fbidi \fmodern\fcharset162\fprq1 Courier New Tur;}{\f64\fbidi \fmodern\fcharset177\fprq1 Courier New (Hebrew);}{\f65\fbidi \fmodern\fcharset178\fprq1 Courier New (Arabic);}
{\f66\fbidi \fmodern\fcharset186\fprq1 Courier New Baltic;}{\f67\fbidi \fmodern\fcharset163\fprq1 Courier New (Vietnamese);}{\f379\fbidi \froman\fcharset238\fprq2 Cambria Math CE;}{\f380\fbidi \froman\fcharset204\fprq2 Cambria Math Cyr;}
{\f382\fbidi \froman\fcharset161\fprq2 Cambria Math Greek;}{\f383\fbidi \froman\fcharset162\fprq2 Cambria Math Tur;}{\f386\fbidi \froman\fcharset186\fprq2 Cambria Math Baltic;}{\f387\fbidi \froman\fcharset163\fprq2 Cambria Math (Vietnamese);}
{\flomajor\f31508\fbidi \froman\fcharset238\fprq2 Times New Roman CE;}{\flomajor\f31509\fbidi \froman\fcharset204\fprq2 Times New Roman Cyr;}{\flomajor\f31511\fbidi \froman\fcharset161\fprq2 Times New Roman Greek;}
{\flomajor\f31512\fbidi \froman\fcharset162\fprq2 Times New Roman Tur;}{\flomajor\f31513\fbidi \froman\fcharset177\fprq2 Times New Roman (Hebrew);}{\flomajor\f31514\fbidi \froman\fcharset178\fprq2 Times New Roman (Arabic);}
{\flomajor\f31515\fbidi \froman\fcharset186\fprq2 Times New Roman Baltic;}{\flomajor\f31516\fbidi \froman\fcharset163\fprq2 Times New Roman (Vietnamese);}{\fdbmajor\f31518\fbidi \froman\fcharset238\fprq2 Times New Roman CE;}
{\fdbmajor\f31519\fbidi \froman\fcharset204\fprq2 Times New Roman Cyr;}{\fdbmajor\f31521\fbidi \froman\fcharset161\fprq2 Times New Roman Greek;}{\fdbmajor\f31522\fbidi \froman\fcharset162\fprq2 Times New Roman Tur;}
{\fdbmajor\f31523\fbidi \froman\fcharset177\fprq2 Times New Roman (Hebrew);}{\fdbmajor\f31524\fbidi \froman\fcharset178\fprq2 Times New Roman (Arabic);}{\fdbmajor\f31525\fbidi \froman\fcharset186\fprq2 Times New Roman Baltic;}
{\fdbmajor\f31526\fbidi \froman\fcharset163\fprq2 Times New Roman (Vietnamese);}{\fhimajor\f31528\fbidi \froman\fcharset238\fprq2 Cambria CE;}{\fhimajor\f31529\fbidi \froman\fcharset204\fprq2 Cambria Cyr;}
{\fhimajor\f31531\fbidi \froman\fcharset161\fprq2 Cambria Greek;}{\fhimajor\f31532\fbidi \froman\fcharset162\fprq2 Cambria Tur;}{\fhimajor\f31535\fbidi \froman\fcharset186\fprq2 Cambria Baltic;}
{\fhimajor\f31536\fbidi \froman\fcharset163\fprq2 Cambria (Vietnamese);}{\fbimajor\f31538\fbidi \froman\fcharset238\fprq2 Times New Roman CE;}{\fbimajor\f31539\fbidi \froman\fcharset204\fprq2 Times New Roman Cyr;}
{\fbimajor\f31541\fbidi \froman\fcharset161\fprq2 Times New Roman Greek;}{\fbimajor\f31542\fbidi \froman\fcharset162\fprq2 Times New Roman Tur;}{\fbimajor\f31543\fbidi \froman\fcharset177\fprq2 Times New Roman (Hebrew);}
{\fbimajor\f31544\fbidi \froman\fcharset178\fprq2 Times New Roman (Arabic);}{\fbimajor\f31545\fbidi \froman\fcharset186\fprq2 Times New Roman Baltic;}{\fbimajor\f31546\fbidi \froman\fcharset163\fprq2 Times New Roman (Vietnamese);}
{\flominor\f31548\fbidi \froman\fcharset238\fprq2 Times New Roman CE;}{\flominor\f31549\fbidi \froman\fcharset204\fprq2 Times New Roman Cyr;}{\flominor\f31551\fbidi \froman\fcharset161\fprq2 Times New Roman Greek;}
{\flominor\f31552\fbidi \froman\fcharset162\fprq2 Times New Roman Tur;}{\flominor\f31553\fbidi \froman\fcharset177\fprq2 Times New Roman (Hebrew);}{\flominor\f31554\fbidi \froman\fcharset178\fprq2 Times New Roman (Arabic);}
{\flominor\f31555\fbidi \froman\fcharset186\fprq2 Times New Roman Baltic;}{\flominor\f31556\fbidi \froman\fcharset163\fprq2 Times New Roman (Vietnamese);}{\fdbminor\f31558\fbidi \froman\fcharset238\fprq2 Times New Roman CE;}
{\fdbminor\f31559\fbidi \froman\fcharset204\fprq2 Times New Roman Cyr;}{\fdbminor\f31561\fbidi \froman\fcharset161\fprq2 Times New Roman Greek;}{\fdbminor\f31562\fbidi \froman\fcharset162\fprq2 Times New Roman Tur;}
{\fdbminor\f31563\fbidi \froman\fcharset177\fprq2 Times New Roman (Hebrew);}{\fdbminor\f31564\fbidi \froman\fcharset178\fprq2 Times New Roman (Arabic);}{\fdbminor\f31565\fbidi \froman\fcharset186\fprq2 Times New Roman Baltic;}
{\fdbminor\f31566\fbidi \froman\fcharset163\fprq2 Times New Roman (Vietnamese);}{\fhiminor\f31568\fbidi \fswiss\fcharset238\fprq2 Calibri CE;}{\fhiminor\f31569\fbidi \fswiss\fcharset204\fprq2 Calibri Cyr;}
{\fhiminor\f31571\fbidi \fswiss\fcharset161\fprq2 Calibri Greek;}{\fhiminor\f31572\fbidi \fswiss\fcharset162\fprq2 Calibri Tur;}{\fhiminor\f31575\fbidi \fswiss\fcharset186\fprq2 Calibri Baltic;}
{\fhiminor\f31576\fbidi \fswiss\fcharset163\fprq2 Calibri (Vietnamese);}{\fbiminor\f31578\fbidi \froman\fcharset238\fprq2 Times New Roman CE;}{\fbiminor\f31579\fbidi \froman\fcharset204\fprq2 Times New Roman Cyr;}
{\fbiminor\f31581\fbidi \froman\fcharset161\fprq2 Times New Roman Greek;}{\fbiminor\f31582\fbidi \froman\fcharset162\fprq2 Times New Roman Tur;}{\fbiminor\f31583\fbidi \froman\fcharset177\fprq2 Times New Roman (Hebrew);}
{\fbiminor\f31584\fbidi \froman\fcharset178\fprq2 Times New Roman (Arabic);}{\fbiminor\f31585\fbidi \froman\fcharset186\fprq2 Times New Roman Baltic;}{\fbiminor\f31586\fbidi \froman\fcharset163\fprq2 Times New Roman (Vietnamese);}}
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\red128\green0\blue128;\red128\green0\blue0;\red128\green128\blue0;\red128\green128\blue128;\red192\green192\blue192;}{\*\defchp \f31506\fs22 }{\*\defpap \ql \li0\ri0\sa200\sl276\slmult1
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{\*\rsidtbl \rsid330752\rsid863134\rsid932563\rsid1271518\rsid1716191\rsid3364447\rsid3539692\rsid4200218\rsid5456577\rsid6637072\rsid7145210\rsid7497065\rsid8142758\rsid8796292\rsid9655377\rsid12134742\rsid13391001\rsid14576707\rsid14578815\rsid14695677
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{\creatim\yr2012\mo5\dy27\hr17\min18}{\revtim\yr2012\mo5\dy27\hr17\min52}{\version7}{\edmins18}{\nofpages3}{\nofwords650}{\nofchars3710}{\*\company Microsoft}{\nofcharsws4352}{\vern32773}}{\*\xmlnstbl {\xmlns1 http://schemas.microsoft.com/office/word/2003
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\widowctrl\ftnbj\aenddoc\trackmoves1\trackformatting1\donotembedsysfont1\relyonvml0\donotembedlingdata0\grfdocevents0\validatexml1\showplaceholdtext0\ignoremixedcontent0\saveinvalidxml0\showxmlerrors1\noxlattoyen
\expshrtn\noultrlspc\dntblnsbdb\nospaceforul\formshade\horzdoc\dgmargin\dghspace180\dgvspace180\dghorigin1440\dgvorigin1440\dghshow1\dgvshow1
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\asianbrkrule\rsidroot15740007\newtblstyruls\nogrowautofit\usenormstyforlist\noindnmbrts\felnbrelev\nocxsptable\indrlsweleven\noafcnsttbl\afelev\utinl\hwelev\spltpgpar\notcvasp\notbrkcnstfrctbl\notvatxbx\krnprsnet\cachedcolbal \nouicompat \fet0
{\*\wgrffmtfilter 2450}\nofeaturethrottle1\ilfomacatclnup0\ltrpar \sectd \ltrsect\linex0\endnhere\sectlinegrid360\sectdefaultcl\sectrsid8796292\sftnbj {\*\pnseclvl1\pnucrm\pnstart1\pnindent720\pnhang {\pntxta .}}{\*\pnseclvl2
\pnucltr\pnstart1\pnindent720\pnhang {\pntxta .}}{\*\pnseclvl3\pndec\pnstart1\pnindent720\pnhang {\pntxta .}}{\*\pnseclvl4\pnlcltr\pnstart1\pnindent720\pnhang {\pntxta )}}{\*\pnseclvl5\pndec\pnstart1\pnindent720\pnhang {\pntxtb (}{\pntxta )}}{\*\pnseclvl6
\pnlcltr\pnstart1\pnindent720\pnhang {\pntxtb (}{\pntxta )}}{\*\pnseclvl7\pnlcrm\pnstart1\pnindent720\pnhang {\pntxtb (}{\pntxta )}}{\*\pnseclvl8\pnlcltr\pnstart1\pnindent720\pnhang {\pntxtb (}{\pntxta )}}{\*\pnseclvl9\pnlcrm\pnstart1\pnindent720\pnhang
{\pntxtb (}{\pntxta )}}\pard\plain \ltrpar\ql \li0\ri0\sl480\slmult1\nowidctlpar\wrapdefault\faauto\rin0\lin0\itap0\pararsid15152912 \rtlch\fcs1 \af31507\afs22\alang1025 \ltrch\fcs0
\fs22\lang1033\langfe1033\loch\af31506\hich\af31506\dbch\af31505\cgrid\langnp1033\langfenp1033 {\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid15740007\charrsid9655377 \hich\af2\dbch\af31505\loch\f2 Kareem Francis
\par \hich\af2\dbch\af31505\loch\f2 Naive Bayes Article Classifier
\par \hich\af2\dbch\af31505\loch\f2 5/2}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid15163970 \hich\af2\dbch\af31505\loch\f2 7}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid15740007\charrsid9655377 \hich\af2\dbch\af31505\loch\f2 /12
\par \hich\af2\dbch\af31505\loch\f2 CS363 Artificial Intelligence
\par \hich\af2\dbch\af31505\loch\f2 CUNY Queens College
\par }\pard \ltrpar\qc \li0\ri0\sa200\sl480\slmult1\widctlpar\wrapdefault\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid15152912 {\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid15740007\charrsid9655377 \hich\af2\dbch\af31505\loch\f2 Performance Results}{
\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid8796292\charrsid9655377
\par }\pard \ltrpar\ql \li0\ri0\sa200\sl480\slmult1\widctlpar\wrapdefault\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid15152912 {\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid16133078 \hich\af2\dbch\af31505\loch\f2 Foreword: the t}{\rtlch\fcs1 \af2
\ltrch\fcs0 \f2\insrsid330752 \hich\af2\dbch\af31505\loch\f2 ra\hich\af2\dbch\af31505\loch\f2
ining data is prone to over fitting because of the way that Google news aggregates articles. Articles from the same time period in the same topic will have very similar content, }{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid16409986
\hich\af2\dbch\af31505\loch\f2 because multiple publications will run the same trending stories}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid330752 \hich\af2\dbch\af31505\loch\f2 . The articles\hich\af2\dbch\af31505\loch\f2
gathered by the web crawler were all gathered within a few minutes of each other. }{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid1271518
\par }{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid9655377 \hich\af2\dbch\af31505\loch\f2 Classification:
\par }\pard \ltrpar\ql \fi720\li0\ri0\sa200\sl480\slmult1\widctlpar\wrapdefault\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid16409986 {\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid9655377 \hich\af2\dbch\af31505\loch\f2 On the set of }{\rtlch\fcs1
\af2 \ltrch\fcs0 \f2\insrsid6637072 \hich\af2\dbch\af31505\loch\f2 442 }{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid9655377 \hich\af2\dbch\af31505\loch\f2 articles that I gathered from Google news,}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid6637072
\hich\af2\dbch\af31505\loch\f2 100 were used for testing, and the rest for training.}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid9655377 \hich\af2\dbch\af31505\loch\f2
I found that overall accuracy and classification accuracy, as well as program execution time, was }{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid13391001 \hich\af2\dbch\af31505\loch\f2 m\hich\af2\dbch\af31505\loch\f2 ost }{\rtlch\fcs1 \af2 \ltrch\fcs0
\f2\insrsid9655377 \hich\af2\dbch\af31505\loch\f2 heavily dependent on the technique utilized f}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid1716191 \hich\af2\dbch\af31505\loch\f2
or preprocessing articles. I tried varies methods of preprocessing text, which are described in the project outline. }{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid9655377
\par }\pard \ltrpar\ql \li0\ri0\sa200\sl480\slmult1\widctlpar\wrapdefault\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid15152912 {\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid1716191 \tab \hich\af2\dbch\af31505\loch\f2
Using the stop words list in the source folder, the overall accuracy was 89%}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid12134742 \hich\af2\dbch\af31505\loch\f2 . The indivi\hich\af2\dbch\af31505\loch\f2
dual accuracies were 100%, 100%, 95%, 80% and 70% for sports, health, entertainment, technology, and business, respectively. The low accuracy for business can be attributed to the fact that there was an uneven distribution of articles. While the other cat
\hich\af2\dbch\af31505\loch\f2 e\hich\af2\dbch\af31505\loch\f2 gories composed ~20-23% each, business comprised only about 15%. }{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid863134
\par }\pard \ltrpar\ql \fi720\li0\ri0\sa200\sl480\slmult1\widctlpar\wrapdefault\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid863134 {\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid12134742 \hich\af2\dbch\af31505\loch\f2 The Natural Language Toolkit}{
\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid13391001 \hich\af2\dbch\af31505\loch\f2 stop word list}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid12134742 \hich\af2\dbch\af31505\loch\f2 }{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid863134
\hich\af2\dbch\af31505\loch\f2 produced 74% overall and The individual accuracies were 100%, 85%, 70%, 70% and 45% for sports, health, entertainment, technology, and business, r\hich\af2\dbch\af31505\loch\f2
espectively. It takes about twice as long to run as the above technique}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid16409986 .}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid330752
\par }\pard \ltrpar\ql \fi720\li0\ri0\sa200\sl480\slmult1\widctlpar\wrapdefault\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid8142758 {\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid16409986 \hich\af2\dbch\af31505\loch\f2 The last }{\rtlch\fcs1 \af2
\ltrch\fcs0 \f2\insrsid13391001 \hich\af2\dbch\af31505\loch\f2 preprocessing }{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid16409986 \hich\af2\dbch\af31505\loch\f2 technique that produced viable results was}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid330752
\hich\af2\dbch\af31505\loch\f2 part of speech tagging, again making use of the NLTK. This technique takes significantly to execute than the }{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid7497065 \hich\af2\dbch\af31505\loch\f2 other tw
\hich\af2\dbch\af31505\loch\f2 o}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid13391001 \hich\af2\dbch\af31505\loch\f2 , and is very processor intensive}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid7497065 .}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid932563
\hich\af2\dbch\af31505\loch\f2 This was the reason I implemented execution serialization, so as not to have to avoid having to re-process this information between executions.}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid7497065
\hich\af2\dbch\af31505\loch\f2 D}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid15163970 \hich\af2\dbch\af31505\loch\f2 epending on the testing set, may produce }{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid13391001 \hich\af2\dbch\af31505\loch\f2 near }{
\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid15163970 \hich\af2\dbch\af31505\loch\f2 identical results }{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid13391001 \hich\af2\dbch\af31505\loch\f2 and as much\hich\af2\dbch\af31505\loch\f2 as 10% higher}{\rtlch\fcs1 \af2
\ltrch\fcs0 \f2\insrsid3364447 \hich\af2\dbch\af31505\loch\f2 }{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid13391001 \hich\af2\dbch\af31505\loch\f2 than}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid15163970 \hich\af2\dbch\af31505\loch\f2 t}{\rtlch\fcs1 \af2
\ltrch\fcs0 \f2\insrsid3364447 \hich\af2\dbch\af31505\loch\f2 hat of the NLTK stop word list}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid13391001 \hich\af2\dbch\af31505\loch\f2 , from my experimentation}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid3364447 .}{
\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid13391001 \hich\af2\dbch\af31505\loch\f2 It produces 76% overall accuracy on current data, with 100%, 85%, 75%, 80% and 40% for sports, health, entertainment, technology, and business, respectively.}{\rtlch\fcs1
\af2 \ltrch\fcs0 \f2\insrsid12134742
\par }{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid13391001 \hich\af2\dbch\af31505\loch\f2
I also attempted to implement ensemble classification, using N Bayesian models instead of just one. This was done by splitting the training data into N unique subset, and training each model independently. However, the results lagged behind those of the s
\hich\af2\dbch\af31505\loch\f2 i\hich\af2\dbch\af31505\loch\f2 ngle model classifier, and further research would have been necessary to produce a more viable system.
\par }{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid8142758\charrsid9655377
\par }\pard \ltrpar\ql \li0\ri0\sa200\sl480\slmult1\widctlpar\wrapdefault\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid15152912 {\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid15740007\charrsid9655377 \hich\af2\dbch\af31505\loch\f2 Clustering:
\par }\pard \ltrpar\ql \fi720\li0\ri0\sa200\sl480\slmult1\widctlpar\wrapdefault\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid8142758 {\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid14576707\charrsid9655377 \hich\af2\dbch\af31505\loch\f2
As a side effect of using a prebuilt K-Means algorithm, I had to strip the article IDs, }{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid9655377\charrsid9655377 \hich\af2\dbch\af31505\loch\f2 and then}{\rtlch\fcs1 \af2 \ltrch\fcs0
\f2\insrsid14576707\charrsid9655377 \hich\af2\dbch\af31505\loch\f2 }{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid14695677\charrsid9655377 \hich\af2\dbch\af31505\loch\f2 reattach}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid14576707\charrsid9655377
\hich\af2\dbch\af31505\loch\f2 them in a later step. This proces\hich\af2\dbch\af31505\loch\f2
s is detrimental to the execution time. However, it does takes roughly one minute to cluster 100 articles on a modern computer. When clustering into five means, as many as 16/20 articles of the same category are clustered together. I also experimente}{
\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid15678288\charrsid9655377 \hich\af2\dbch\af31505\loch\f2 d with\hich\af2\dbch\af31505\loch\f2
the number of iterations to find the best means, between one and ten, but found that generally, the results did not diverge greatly.}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid15152912
\par }{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid15152912\charrsid9655377 \hich\af2\dbch\af31505\loch\f2 In the }{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid15152912 \hich\af2\dbch\af31505\loch\f2 below}{\rtlch\fcs1 \af2 \ltrch\fcs0
\f2\insrsid15152912\charrsid9655377 \hich\af2\dbch\af31505\loch\f2 clustering instance, which was produced after only one iteration, it Group 2 consists almost exclusively of e\hich\af2\dbch\af31505\loch\f2
ntertainment articles. In fact, it contains 17/20 of the total entertainment test articles. Not too far off is Group 1, of which 9/10 of its members are technology articles, constituting 50% of the overall tech articles. Group 3 contains 100% of the spor
\hich\af2\dbch\af31505\loch\f2 t\hich\af2\dbch\af31505\loch\f2 s articles, but is also mixed in with other classes of articles. These results are surprisingly good.}{\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid14576707\charrsid9655377
\par }\pard \ltrpar\ql \li0\ri0\sa200\widctlpar\wrapdefault\aspalpha\aspnum\faauto\adjustright\rin0\lin0\itap0\pararsid3539692 {\rtlch\fcs1 \af2 \ltrch\fcs0 \f2\insrsid14576707\charrsid9655377 \hich\af2\dbch\af31505\loch\f2 Sample clustering output:
\par \hich\af2\dbch\af31505\loch\f2 Group 0: ['137', '136', '135', '134', '139', '138', '140', '7', '304', '245', '102', '103', '249', '248', '104', '105', '247', '\hich\af2\dbch\af31505\loch\f2 106', '2', '6', '355', '350']
\par \hich\af2\dbch\af31505\loch\f2 Group 1: ['210', '194', '250', '201', '200', '203', '202', '207', '206', '209', '208']
\par \hich\af2\dbch\af31505\loch\f2 Group 2: ['22', '4', '8', '110', '3', '11', '10', '13', '12', '15', '14', '17', '16', '19', '18', '1', '5', '9']
\par \hich\af2\dbch\af31505\loch\f2
Group 3: ['133', '407', '406', '405', '404', '403', '401', '400', '409', '408', '410', '310', '360', '308', '309', '440', '300', '306', '307', '244', '109', '241', '240', '243', '242', '438', '439', '436', '437', '434', '430', '431', '335', '334', '107',
\hich\af2\dbch\af31505\loch\f2 '\hich\af2\dbch\af31505\loch\f2 402']
\par \hich\af2\dbch\af31505\loch\f2 Group 4: ['132', '131', '130', '301', '302', '303', '305', '108', '356', '354', '353', '352', '351']
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