项目作者: lffloyd

项目描述 :
Scripts, datasets e utilitários para modelagem e identificação de tópicos relativos a depressão no Reddit usando Latent Dirichlet Allocation (LDA).
高级语言: Jupyter Notebook
项目地址: git://github.com/lffloyd/reddit-topic-modelling.git
创建时间: 2020-07-18T01:57:45Z
项目社区:https://github.com/lffloyd/reddit-topic-modelling

开源协议:MIT License

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CTM_K=8_tsne_1649671534153.pdf
ETM_K=28_tsne_1649671534195.pdf
LDA_K=15_tsne_1649671534243.pdf
coherence_by_k_1649671534306.pdf
ctm_topic=1_1649671534351.pdf
ctm_topic=2_1649671534388.pdf
ctm_topic=3_1649671534413.pdf
ctm_topic=4_1649671534417.pdf
ctm_topic=5_1649671534460.pdf
ctm_topic=6_1649671534475.pdf
ctm_topic=7_1649671534483.pdf
ctm_topic=8_1649671534486.pdf
en_coherence_by_k_1649671534497.pdf
en_lexical_analysis_1649671534517.pdf
etm_topic=1_1649671534570.pdf
etm_topic=10_1649671534666.pdf
etm_topic=11_1649671534699.pdf
etm_topic=12_1649671534702.pdf
etm_topic=13_1649671534726.pdf
etm_topic=14_1649671534752.pdf
etm_topic=15_1649671534796.pdf
etm_topic=16_1649671534820.pdf
etm_topic=17_1649671534839.pdf
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etm_topic=6_1649671535487.pdf
etm_topic=7_1649671535490.pdf
etm_topic=8_1649671535522.pdf
etm_topic=9_1649671535560.pdf
lda_topic=1_1649671535580.pdf
lda_topic=10_1649671535601.pdf
lda_topic=11_1649671535604.pdf
lda_topic=12_1649671535623.pdf
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lda_topic=15_1649671535721.pdf
lda_topic=2_1649671535725.pdf
lda_topic=3_1649671535767.pdf
lda_topic=4_1649671535800.pdf
lda_topic=5_1649671535820.pdf
lda_topic=6_1649671535822.pdf
lda_topic=7_1649671535847.pdf
lda_topic=8_1649671535869.pdf
lda_topic=9_1649671535891.pdf
lexical_analysis_1649671535910.pdf
CTM_K=20_tsne_1649671538546.pdf
ETM_K=5_tsne_1649671538587.pdf
LDA_K=5_tsne._1649671538613.pdf
LDA_K=5_tsne_1649671538646.pdf
coherence_by_k._1649671538668.pdf
coherence_by_k_1649671538713.pdf
ctm_topic=1_1649671538739.pdf
ctm_topic=10_1649671538758.pdf
ctm_topic=11_1649671538760.pdf
ctm_topic=12_1649671538774.pdf
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ctm_topic=14_1649671538831.pdf
ctm_topic=15_1649671538863.pdf
ctm_topic=16_1649671538886.pdf
ctm_topic=17_1649671538915.pdf
ctm_topic=18_1649671538930.pdf
ctm_topic=19_1649671538963.pdf
ctm_topic=2_1649671539011.pdf
ctm_topic=20_1649671539059.pdf
ctm_topic=3_1649671539144.pdf
ctm_topic=4_1649671539148.pdf
ctm_topic=5_1649671539177.pdf
ctm_topic=6_1649671539180.pdf
ctm_topic=7_1649671539232.pdf
ctm_topic=8_1649671539276.pdf
ctm_topic=9_1649671539309.pdf
etm_topic=1_1649671539328.pdf
etm_topic=2_1649671539338.pdf
etm_topic=3_1649671539357.pdf
etm_topic=4_1649671539373.pdf
etm_topic=5_1649671539377.pdf
lda_topic=1_1649671539401.pdf
lda_topic=2_1649671539420.pdf
lda_topic=3_1649671539439.pdf
lda_topic=4_1649671539460.pdf
lda_topic=5_1649671539519.pdf
lexical_analysis_1649671539561.pdf
histPt_1649671539565.pdf
histogram_pt_0_to_7__1649671539638.pdf
pt_coherence_by_k_1649671539697.pdf
pt_lexical_analysis_1649671539732.pdf
lda_topic=5_1647610857330.pdf