35 lines
1.7 KiB
Bash
35 lines
1.7 KiB
Bash
#!/usr/bin/env bash
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dataset=/home/moreo/CLESA/jrc_acquis/jrc_doclist_1958-2005vs2006_all_top300_noparallel_processed_run0.pickle
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logfile=./results/final_combinations_jrc.csv
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#A.2: ensembling feature sets (combinations of posteriors, wce, muse):
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# - exploring different ways of putting different feature sets together: concatenation, FeatureSetToPosteriors, averaging, voting, etc...
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# (no one seems to improve over standard funnelling [the improved version after A.1] with posteriors probabilities...)
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# aggregation=concatenation
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#python main_gFun.py $dataset -o $logfile -P -U -r -z --l2
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#python main_gFun.py $dataset -o $logfile -P -S -r -z --l2
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#python main_gFun.py $dataset -o $logfile -U -S -r -z --l2
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#python main_gFun.py $dataset -o $logfile -P -U -S -r -z --l2
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#
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##FeatureSetToPosteriors (aggregation mean)
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python main_multimodal_cls.py $dataset -o $logfile -P -U -r -a -z --l2 --allprob
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python main_multimodal_cls.py $dataset -o $logfile -P -S -r -a -z --l2 --allprob
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python main_multimodal_cls.py $dataset -o $logfile -U -S -r -a -z --l2 --allprob
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python main_multimodal_cls.py $dataset -o $logfile -P -U -S -r -a -z --l2 --allprob
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##FeatureSetToPosteriors
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#python main_gFun.py $dataset -o $logfile -P -U -r -z --l2 --allprob
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#python main_gFun.py $dataset -o $logfile -P -S -r -z --l2 --allprob
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#python main_gFun.py $dataset -o $logfile -U -S -r -z --l2 --allprob
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#python main_gFun.py $dataset -o $logfile -P -U -S -r -z --l2 --allprob
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#MajorityVoting
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#python main_majorityvoting_cls.py $dataset -o $logfile -P -U -r
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#python main_majorityvoting_cls.py $dataset -o $logfile -P -S -r
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#python main_majorityvoting_cls.py $dataset -o $logfile -U -S -r
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#python main_majorityvoting_cls.py $dataset -o $logfile -P -U -S -r
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