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Aaron Halfaker
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Merging in eu, hu, hy, sr, and uk models from Haksoat
2 parents 8ca8074 + 66bd816 commit 563e3e6

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‎Makefile‎

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.DELETE_ON_ERROR:
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drafttopic_major_minor = 1.3
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drafttopic_major_minor = 1.4
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models: \
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articletopic_models \
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drafttopic_models
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drafttopic_models: \
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models/arwiki.drafttopic.gradient_boosting.model \
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models/cswiki.drafttopic.gradient_boosting.model \
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models/enwiki.drafttopic.gradient_boosting.model \
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models/kowiki.drafttopic.gradient_boosting.model \
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models/viwiki.drafttopic.gradient_boosting.model
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models/hywiki.drafttopic.gradient_boosting.model
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articletopic_models: \
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models/arwiki.articletopic.gradient_boosting.model \
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models/cswiki.articletopic.gradient_boosting.model \
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models/enwiki.articletopic.gradient_boosting.model \
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models/kowiki.articletopic.gradient_boosting.model \
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models/viwiki.articletopic.gradient_boosting.model \
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models/wikidata.articletopic.gradient_boosting.model
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models/wikidata.articletopic.gradient_boosting.model \
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models/hywiki.articletopic.gradient_boosting.model
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tuning_models: \
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tuning_reports/hywiki.articletopic.md \
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tuning_reports/hywiki.drafttopic.md
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# Johnson, Isaac; Halfaker, Aaron (2019):
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# Wikipedia Articles and Associated WikiProject Templates. figshare. Dataset.
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# https://doi.org/10.6084/m9.figshare.10248344.v3
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datasets/enwiki.article_items_with_wikiproject_templates.20191201.json.bz2:
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wget https://ndownloader.figshare.com/files/20183063 -qO- > $@
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@@ -58,163 +55,54 @@ labels-config.json: \
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datasets/enwiki.labeled_article_items.json.bz2
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bzcat $< | ./utility write_labels taxo_labels > $@
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###################### Arabic Wikipedia ##########################
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datasets/arwiki.balanced_article_sample.json: \
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datasets/hywiki.balanced_article_sample.json: \
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datasets/enwiki.labeled_article_items.json.bz2
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bzcat $< | ./utility balance_sample ar -n 1000 > $@
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bzcat $< | ./utility balance_sample hy -n 1000 > $@
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datasets/arwiki.balanced_article_sample.w_draft_text.json: \
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datasets/arwiki.balanced_article_sample.json
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datasets/hywiki.balanced_article_sample.w_draft_text.json: \
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datasets/hywiki.balanced_article_sample.json
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./utility fetch_draft_text \
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--api-host=https://ar.wikipedia.org \
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--api-host=https://hy.wikipedia.org \
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--input=$< \
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--output=$@ \
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--debug
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datasets/arwiki.balanced_article_sample.w_article_text.json: \
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datasets/arwiki.balanced_article_sample.json
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datasets/hywiki.balanced_article_sample.w_article_text.json: \
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datasets/hywiki.balanced_article_sample.json
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./utility fetch_article_text \
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--api-host=https://ar.wikipedia.org \
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--api-host=https://hy.wikipedia.org \
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--input=$< \
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--output=$@ \
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--debug
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#word2vec/hywiki-20200501-learned_vectors.50_cell.10k.kv:
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# wget https://analytics.wikimedia.org/datasets/archive/public-datasets/all/ores/topic/vectors/hywiki-20200501-learned_vectors.50_cell.10k.kv -qO- > $@
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word2vec/arwiki-20200501-learned_vectors.50_cell.10k.kv:
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wget https://analytics.wikimedia.org/datasets/archive/public-datasets/all/ores/topic/vectors/arwiki-20200501-learned_vectors.50_cell.10k.kv -qO- > $@
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datasets/arwiki.balanced_article_sample.w_draft_cache.json: \
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datasets/arwiki.balanced_article_sample.w_draft_text.json \
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word2vec/arwiki-20200501-learned_vectors.50_cell.10k.kv
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datasets/hywiki.balanced_article_sample.w_draft_cache.json: \
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datasets/hywiki.balanced_article_sample.w_draft_text.json \
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word2vec/hywiki-20200501-learned_vectors.50_cell.10k.kv
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./utility extract_from_text \
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drafttopic.feature_lists.arwiki.drafttopic \
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drafttopic.feature_lists.hywiki.drafttopic \
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--input=$< \
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--output=$@ \
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--verbose
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datasets/arwiki.balanced_article_sample.w_article_cache.json: \
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datasets/arwiki.balanced_article_sample.w_article_text.json \
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word2vec/arwiki-20200501-learned_vectors.50_cell.10k.kv
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datasets/hywiki.balanced_article_sample.w_article_cache.json: \
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datasets/hywiki.balanced_article_sample.w_article_text.json \
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word2vec/hywiki-20200501-learned_vectors.50_cell.10k.kv
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./utility extract_from_text \
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drafttopic.feature_lists.arwiki.articletopic \
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drafttopic.feature_lists.hywiki.articletopic \
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--input=$< \
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--output=$@ \
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--verbose
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models/arwiki.drafttopic.gradient_boosting.model: \
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datasets/arwiki.balanced_article_sample.w_draft_cache.json \
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labels-config.json
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cat $< | \
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revscoring cv_train revscoring.scoring.models.GradientBoosting \
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drafttopic.feature_lists.arwiki.drafttopic taxo_labels \
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--debug \
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--labels-config=labels-config.json \
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-p 'n_estimators=150' \
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-p 'max_depth=5' \
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-p 'max_features="log2"' \
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-p 'learning_rate=0.1' \
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--version=$(drafttopic_major_minor).0 \
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--folds=5 \
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--multilabel > $@
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revscoring model_info $@ > model_info/arwiki.drafttopic.md
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models/arwiki.articletopic.gradient_boosting.model: \
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datasets/arwiki.balanced_article_sample.w_article_cache.json \
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labels-config.json
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cat $< | \
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revscoring cv_train revscoring.scoring.models.GradientBoosting \
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drafttopic.feature_lists.arwiki.articletopic taxo_labels \
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--debug \
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--labels-config=labels-config.json \
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-p 'n_estimators=150' \
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-p 'max_depth=5' \
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-p 'max_features="log2"' \
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-p 'learning_rate=0.1' \
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--version=$(drafttopic_major_minor).0 \
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--folds=5 \
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--multilabel > $@
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revscoring model_info $@ > model_info/arwiki.articletopic.md
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tuning_reports/arwiki.drafttopic.md: \
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datasets/arwiki.balanced_article_sample.w_draft_cache.json
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cat $< | \
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revscoring tune config/gradient_boosting.params.yaml \
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drafttopic.feature_lists.arwiki.drafttopic \
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taxo_labels pr_auc.macro \
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--debug \
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--verbose \
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--multilabel \
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--labels-config=labels-config.yaml \
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--folds=3 > $@
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tuning_reports/arwiki.articletopic.md: \
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datasets/arwiki.balanced_article_sample.w_article_cache.json
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cat $< | \
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revscoring tune config/gradient_boosting.params.yaml \
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drafttopic.feature_lists.arwiki.articletopic \
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taxo_labels pr_auc.macro \
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--debug \
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--verbose \
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--multilabel \
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--labels-config=labels-config.yaml \
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--folds=3 > $@
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################### Czech Wikipedia #############################
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datasets/cswiki.balanced_article_sample.json: \
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datasets/enwiki.labeled_article_items.json.bz2
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bzcat $< | ./utility balance_sample cs -n 1000 > $@
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datasets/cswiki.balanced_article_sample.w_draft_text.json: \
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datasets/cswiki.balanced_article_sample.json
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./utility fetch_draft_text \
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--api-host=https://cs.wikipedia.org \
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--input=$< \
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--output=$@ \
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--debug
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datasets/cswiki.balanced_article_sample.w_article_text.json: \
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datasets/cswiki.balanced_article_sample.json
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./utility fetch_article_text \
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--api-host=https://cs.wikipedia.org \
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--input=$< \
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--output=$@ \
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--debug
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word2vec/cswiki-20200501-learned_vectors.50_cell.10k.kv:
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wget https://analytics.wikimedia.org/datasets/archive/public-datasets/all/ores/topic/vectors/cswiki-20200501-learned_vectors.50_cell.10k.kv -qO- > $@
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datasets/cswiki.balanced_article_sample.w_draft_cache.json: \
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datasets/cswiki.balanced_article_sample.w_draft_text.json \
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word2vec/cswiki-20200501-learned_vectors.50_cell.10k.kv
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./utility extract_from_text \
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drafttopic.feature_lists.cswiki.drafttopic \
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--input=$< \
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--output=$@ \
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--verbose
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datasets/cswiki.balanced_article_sample.w_article_cache.json: \
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datasets/cswiki.balanced_article_sample.w_article_text.json \
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word2vec/cswiki-20200501-learned_vectors.50_cell.10k.kv
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./utility extract_from_text \
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drafttopic.feature_lists.cswiki.articletopic \
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--input=$< \
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--output=$@ \
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--verbose
21199

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models/cswiki.drafttopic.gradient_boosting.model: \
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datasets/cswiki.balanced_article_sample.w_draft_cache.json \
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models/hywiki.drafttopic.gradient_boosting.model: \
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datasets/hywiki.balanced_article_sample.w_draft_cache.json \
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labels-config.json
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cat $< | \
216104
revscoring cv_train revscoring.scoring.models.GradientBoosting \
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drafttopic.feature_lists.cswiki.drafttopic taxo_labels \
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drafttopic.feature_lists.hywiki.drafttopic taxo_labels \
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--debug \
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--labels-config=labels-config.json \
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-p 'n_estimators=150' \
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225113
--folds=5 \
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--multilabel > $@
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228-
revscoring model_info $@ > model_info/cswiki.drafttopic.md
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revscoring model_info $@ > model_info/hywiki.drafttopic.md
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models/cswiki.articletopic.gradient_boosting.model: \
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datasets/cswiki.balanced_article_sample.w_article_cache.json \
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models/hywiki.articletopic.gradient_boosting.model: \
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datasets/hywiki.balanced_article_sample.w_article_cache.json \
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labels-config.json
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cat $< | \
234122
revscoring cv_train revscoring.scoring.models.GradientBoosting \
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drafttopic.feature_lists.cswiki.articletopic taxo_labels \
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drafttopic.feature_lists.hywiki.articletopic taxo_labels \
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--debug \
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--labels-config=labels-config.json \
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-p 'n_estimators=150' \
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--folds=5 \
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--multilabel > $@
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revscoring model_info $@ > model_info/cswiki.articletopic.md
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revscoring model_info $@ > model_info/hywiki.articletopic.md
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248136

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tuning_reports/cswiki.drafttopic.md: \
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datasets/cswiki.balanced_article_sample.w_draft_cache.json
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tuning_reports/hywiki.drafttopic.md: \
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datasets/hywiki.balanced_article_sample.w_draft_cache.json
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cat $< | \
252140
revscoring tune config/gradient_boosting.params.yaml \
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drafttopic.feature_lists.cswiki.drafttopic \
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drafttopic.feature_lists.hywiki.drafttopic \
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taxo_labels pr_auc.macro \
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--debug \
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--verbose \
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--multilabel \
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--labels-config=labels-config.json \
259147
--folds=3 > $@
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tuning_reports/cswiki.articletopic.md: \
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datasets/cswiki.balanced_article_sample.w_article_cache.json
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tuning_reports/hywiki.articletopic.md: \
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datasets/hywiki.balanced_article_sample.w_article_cache.json
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cat $< | \
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revscoring tune config/gradient_boosting.params.yaml \
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drafttopic.feature_lists.cswiki.articletopic \
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drafttopic.feature_lists.hywiki.articletopic \
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taxo_labels pr_auc.macro \
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--debug \
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--verbose \

‎docs/reference/drafttopic.feature_lists.rst‎

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:undoc-members:
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:show-inheritance:
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drafttopic.feature\_lists.ukwiki module
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---------------------------------------
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.. automodule:: drafttopic.feature_lists.ukwiki
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:members:
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:undoc-members:
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:show-inheritance:
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drafttopic.feature\_lists.viwiki module
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---------------------------------------
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‎drafttopic/feature_lists/euwiki.py‎

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from revscoring.datasources.meta import vectorizers, mappers
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from revscoring.features import wikitext
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from revscoring.features.meta import aggregators
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euwiki_kvs = vectorizers.word2vec.load_gensim_kv(
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filename="euwiki-20200501-learned_vectors.50_cell.10k.kv", mmap='r')
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def vectorize_words(words):
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return vectorizers.word2vec.vectorize_words(euwiki_kvs, words)
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revision_text_vectors = vectorizers.word2vec(
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mappers.lower_case(wikitext.revision.datasources.words),
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vectorize_words,
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name="revision.text.eu_vectors")
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w2v = aggregators.mean(
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revision_text_vectors,
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vector=True,
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name="revision.text.eu_vectors_mean"
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)
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drafttopic = [w2v]
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articletopic = drafttopic

‎drafttopic/feature_lists/huwiki.py‎

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from revscoring.datasources.meta import vectorizers, mappers
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from revscoring.features import wikitext
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from revscoring.features.meta import aggregators
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huwiki_kvs = vectorizers.word2vec.load_gensim_kv(
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filename="huwiki-20200501-learned_vectors.50_cell.10k.kv", mmap='r')
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def vectorize_words(words):
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return vectorizers.word2vec.vectorize_words(huwiki_kvs, words)
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revision_text_vectors = vectorizers.word2vec(
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mappers.lower_case(wikitext.revision.datasources.words),
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vectorize_words,
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name="revision.text.hu_vectors")
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w2v = aggregators.mean(
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revision_text_vectors,
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vector=True,
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name="revision.text.hu_vectors_mean"
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)
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drafttopic = [w2v]
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articletopic = drafttopic

‎drafttopic/feature_lists/hywiki.py‎

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from revscoring.datasources.meta import vectorizers, mappers
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from revscoring.features import wikitext
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from revscoring.features.meta import aggregators
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hywiki_kvs = vectorizers.word2vec.load_gensim_kv(
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filename="hywiki-20200501-learned_vectors.50_cell.10k.kv", mmap='r')
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def vectorize_words(words):
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return vectorizers.word2vec.vectorize_words(hywiki_kvs, words)
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revision_text_vectors = vectorizers.word2vec(
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mappers.lower_case(wikitext.revision.datasources.words),
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vectorize_words,
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name="revision.text.hy_vectors")
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w2v = aggregators.mean(
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revision_text_vectors,
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vector=True,
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name="revision.text.hy_vectors_mean"
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)
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drafttopic = [w2v]
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articletopic = drafttopic

‎drafttopic/feature_lists/srwiki.py‎

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from revscoring.datasources.meta import vectorizers, mappers
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from revscoring.features import wikitext
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from revscoring.features.meta import aggregators
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srwiki_kvs = vectorizers.word2vec.load_gensim_kv(
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filename="srwiki-20200501-learned_vectors.50_cell.10k.kv", mmap='r')
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def vectorize_words(words):
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return vectorizers.word2vec.vectorize_words(srwiki_kvs, words)
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revision_text_vectors = vectorizers.word2vec(
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mappers.lower_case(wikitext.revision.datasources.words),
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vectorize_words,
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name="revision.text.sr_vectors")
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w2v = aggregators.mean(
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revision_text_vectors,
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vector=True,
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name="revision.text.sr_vectors_mean"
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)
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drafttopic = [w2v]
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articletopic = drafttopic

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