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diagnostics.xml
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diagnostics.xml
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<?xml version="1.0" encoding="UTF-8"?>
<model>
<topic id='0' tokens='77378.0000' document_entropy='2.1990' word-length='4.1000' coherence='-5.5351' uniform_dist='2.1591' corpus_dist='0.5101' eff_num_words='1055.9381' token-doc-diff='0.0305' rank_1_docs='0.4118' allocation_ratio='0.3529' allocation_count='0.7647' exclusivity='0.8343'>
<word rank='1' count='782' prob='0.01011' cumulative='0.01011' docs='17' word-length='3.0000' coherence='0.0000' uniform_dist='0.0555' corpus_dist='0.0059' token-doc-diff='0.0042' exclusivity='0.8558'>man</word>
<word rank='2' count='451' prob='0.00583' cumulative='0.01593' docs='4' word-length='6.0000' coherence='-1.4450' uniform_dist='0.0288' corpus_dist='0.0038' token-doc-diff='0.0133' exclusivity='0.9999'>holmes</word>
<word rank='3' count='423' prob='0.00547' cumulative='0.02140' docs='15' word-length='4.0000' coherence='-0.1251' uniform_dist='0.0267' corpus_dist='0.0025' token-doc-diff='0.0000' exclusivity='0.7016'>back</word>
<word rank='4' count='420' prob='0.00543' cumulative='0.02683' docs='8' word-length='3.0000' coherence='-0.7531' uniform_dist='0.0264' corpus_dist='0.0035' token-doc-diff='0.0035' exclusivity='0.9909'>sir</word>
<word rank='5' count='404' prob='0.00522' cumulative='0.03205' docs='17' word-length='4.0000' coherence='0.0000' uniform_dist='0.0252' corpus_dist='0.0019' token-doc-diff='0.0005' exclusivity='0.5668'>time</word>
<word rank='6' count='313' prob='0.00405' cumulative='0.03610' docs='16' word-length='4.0000' coherence='-0.0606' uniform_dist='0.0185' corpus_dist='0.0016' token-doc-diff='0.0018' exclusivity='0.6486'>eyes</word>
<word rank='7' count='309' prob='0.00399' cumulative='0.04009' docs='14' word-length='5.0000' coherence='-0.2230' uniform_dist='0.0182' corpus_dist='0.0024' token-doc-diff='0.0008' exclusivity='0.8713'>night</word>
<word rank='8' count='297' prob='0.00384' cumulative='0.04393' docs='17' word-length='4.0000' coherence='0.0000' uniform_dist='0.0174' corpus_dist='0.0025' token-doc-diff='0.0030' exclusivity='0.9999'>face</word>
<word rank='9' count='296' prob='0.00383' cumulative='0.04775' docs='15' word-length='4.0000' coherence='-0.1251' uniform_dist='0.0173' corpus_dist='0.0025' token-doc-diff='0.0016' exclusivity='0.9998'>good</word>
<word rank='10' count='293' prob='0.00379' cumulative='0.05154' docs='15' word-length='4.0000' coherence='-0.1430' uniform_dist='0.0171' corpus_dist='0.0017' token-doc-diff='0.0017' exclusivity='0.7084'>head</word>
</topic>
<topic id='1' tokens='30402.0000' document_entropy='1.8940' word-length='5.9000' coherence='-31.6943' uniform_dist='2.1122' corpus_dist='1.3361' eff_num_words='1228.2388' token-doc-diff='0.0669' rank_1_docs='0.1176' allocation_ratio='0.1333' allocation_count='0.1765' exclusivity='0.9561'>
<word rank='1' count='198' prob='0.00651' cumulative='0.00651' docs='1' word-length='7.0000' coherence='0.0000' uniform_dist='0.0329' corpus_dist='0.0103' token-doc-diff='0.0318' exclusivity='0.9999'>ravager</word>
<word rank='2' count='182' prob='0.00599' cumulative='0.01250' docs='13' word-length='5.0000' coherence='0.0000' uniform_dist='0.0297' corpus_dist='0.0091' token-doc-diff='0.0018' exclusivity='0.9487'>point</word>
<word rank='3' count='162' prob='0.00533' cumulative='0.01783' docs='12' word-length='6.0000' coherence='-0.0800' uniform_dist='0.0259' corpus_dist='0.0059' token-doc-diff='0.0021' exclusivity='0.8040'>matter</word>
<word rank='4' count='145' prob='0.00477' cumulative='0.02260' docs='4' word-length='8.0000' coherence='-1.1769' uniform_dist='0.0226' corpus_dist='0.0076' token-doc-diff='0.0040' exclusivity='0.9999'>smallest</word>
<word rank='5' count='122' prob='0.00401' cumulative='0.02661' docs='7' word-length='3.0000' coherence='-0.6923' uniform_dist='0.0183' corpus_dist='0.0045' token-doc-diff='0.0001' exclusivity='0.8089'>dog</word>
<word rank='6' count='116' prob='0.00382' cumulative='0.03043' docs='9' word-length='6.0000' coherence='-0.3674' uniform_dist='0.0172' corpus_dist='0.0060' token-doc-diff='0.0020' exclusivity='0.9999'>proper</word>
<word rank='7' count='115' prob='0.00378' cumulative='0.03421' docs='11' word-length='4.0000' coherence='-0.3674' uniform_dist='0.0171' corpus_dist='0.0060' token-doc-diff='0.0051' exclusivity='0.9999'>fact</word>
<word rank='8' count='105' prob='0.00345' cumulative='0.03766' docs='1' word-length='5.0000' coherence='-2.5558' uniform_dist='0.0153' corpus_dist='0.0055' token-doc-diff='0.0122' exclusivity='0.9999'>moore</word>
<word rank='9' count='104' prob='0.00342' cumulative='0.04108' docs='3' word-length='8.0000' coherence='-2.4758' uniform_dist='0.0151' corpus_dist='0.0054' token-doc-diff='0.0026' exclusivity='0.9999'>slippers</word>
<word rank='10' count='101' prob='0.00332' cumulative='0.04440' docs='10' word-length='7.0000' coherence='-0.4038' uniform_dist='0.0145' corpus_dist='0.0053' token-doc-diff='0.0051' exclusivity='0.9999'>general</word>
</topic>
<topic id='2' tokens='40320.0000' document_entropy='2.2883' word-length='4.4000' coherence='-9.7591' uniform_dist='1.9006' corpus_dist='1.0364' eff_num_words='1714.9302' token-doc-diff='0.0250' rank_1_docs='0.4706' allocation_ratio='0.4118' allocation_count='0.4706' exclusivity='0.7465'>
<word rank='1' count='237' prob='0.00588' cumulative='0.00588' docs='8' word-length='5.0000' coherence='0.0000' uniform_dist='0.0291' corpus_dist='0.0076' token-doc-diff='0.0141' exclusivity='0.9999'>conan</word>
<word rank='2' count='210' prob='0.00521' cumulative='0.01109' docs='15' word-length='5.0000' coherence='-0.1334' uniform_dist='0.0252' corpus_dist='0.0027' token-doc-diff='0.0013' exclusivity='0.5638'>great</word>
<word rank='3' count='135' prob='0.00335' cumulative='0.01443' docs='15' word-length='4.0000' coherence='-0.1334' uniform_dist='0.0147' corpus_dist='0.0020' token-doc-diff='0.0004' exclusivity='0.6501'>feet</word>
<word rank='4' count='122' prob='0.00303' cumulative='0.01746' docs='9' word-length='4.0000' coherence='-0.5104' uniform_dist='0.0130' corpus_dist='0.0037' token-doc-diff='0.0006' exclusivity='0.9549'>city</word>
<word rank='5' count='119' prob='0.00295' cumulative='0.02041' docs='16' word-length='4.0000' coherence='-0.1334' uniform_dist='0.0126' corpus_dist='0.0001' token-doc-diff='0.0017' exclusivity='0.3662'>made</word>
<word rank='6' count='116' prob='0.00288' cumulative='0.02329' docs='10' word-length='4.0000' coherence='-0.6280' uniform_dist='0.0122' corpus_dist='0.0016' token-doc-diff='0.0001' exclusivity='0.6324'>door</word>
<word rank='7' count='100' prob='0.00248' cumulative='0.02577' docs='12' word-length='5.0000' coherence='-0.4051' uniform_dist='0.0101' corpus_dist='0.0032' token-doc-diff='0.0006' exclusivity='0.9998'>floor</word>
<word rank='8' count='99' prob='0.00246' cumulative='0.02822' docs='14' word-length='5.0000' coherence='-0.2873' uniform_dist='0.0100' corpus_dist='0.0032' token-doc-diff='0.0019' exclusivity='0.9998'>walls</word>
<word rank='9' count='94' prob='0.00233' cumulative='0.03056' docs='10' word-length='4.0000' coherence='-0.5749' uniform_dist='0.0094' corpus_dist='0.0030' token-doc-diff='0.0001' exclusivity='0.9998'>land</word>
<word rank='10' count='94' prob='0.00233' cumulative='0.03289' docs='16' word-length='4.0000' coherence='-0.1334' uniform_dist='0.0094' corpus_dist='-0.0009' token-doc-diff='0.0042' exclusivity='0.2984'>back</word>
</topic>
</model>