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Functions348 in github.com/alexeygrigorev/avito-duplicates-kaggle

⨍ Functions 348◇ Types & classes 9
↓ 2 callersFunctionprepare_batches
(df, n)
calculate_misspelling_features.py:209
↓ 2 callersFunctionprepare_batches
(df, n)
calculate_fuzzy_features.py:27
↓ 2 callersFunctionprepare_batches
(df, n)
calculate_glove_features.py:34
↓ 2 callersFunctionprepare_batches
(df, n)
calculate_w2v_features.py:17
↓ 2 callersFunctionprepare_batches
(df, n)
calculate_ssim_features.py:39
↓ 2 callersFunctionprepare_batches
(df, n)
calculate_important_tokens_features.py:160
↓ 2 callersFunctionprepare_batches
(df, n)
calculate_whash_features.py:38
↓ 2 callersFunctionprepare_batches
(df, n)
calculate_chargram_features.py:57
↓ 2 callersFunctionprepare_batches
(df, n)
calculate_contact_features.py:89
↓ 2 callersFunctionprepare_batches
(df, n)
calculate_attrs_features.py:96
↓ 2 callersFunctionprepare_batches
(df, n)
calculate_imagehash_features.py:17
↓ 2 callersFunctionprepare_batches
(df, n)
calculate_w2v_wmd_features.py:17
↓ 2 callersFunctionprocess_batch
(batch, pool)
calculate_imagemagick_features.py:218
↓ 2 callersFunctionprocess_batch
(batch)
calculate_text_features.py:147
↓ 2 callersFunctionprocess_batch
(batch)
calculate_misspelling_features.py:162
↓ 2 callersFunctionprocess_batch
(batch, pool)
calculate_fuzzy_features.py:39
↓ 2 callersFunctionprocess_batch
(batch, pool)
calculate_glove_features.py:151
↓ 2 callersFunctionprocess_batch
(batch, pool)
calculate_w2v_features.py:182
↓ 2 callersFunctionprocess_batch
(batch, pool)
calculate_ssim_features.py:125
↓ 2 callersFunctionprocess_batch
(batch)
calculate_important_tokens_features.py:111
↓ 2 callersFunctionprocess_batch
(batch, pool)
calculate_whash_features.py:95
↓ 2 callersFunctionprocess_batch
(batch)
calculate_chargram_features.py:83
↓ 2 callersFunctionprocess_batch
(batch)
calculate_contact_features.py:38
↓ 2 callersFunctionprocess_batch
(batch)
calculate_attrs_features.py:72
↓ 2 callersFunctionprocess_batch
(batch, pool)
calculate_imagehash_features.py:136
↓ 2 callersFunctionprocess_batch
(batch, pool)
calculate_w2v_wmd_features.py:109
↓ 2 callersFunctionprocess_file
(source, batch_size, pool)
mongo_put_iteminfo.py:154
↓ 2 callersFunctionprocess_row
(row, train=True)
prepare_common_tokens.py:148
↓ 2 callersFunctionremove_entry
(name, form)
prepare_imagemagick_features.py:60
↓ 2 callersFunctionrow_normalize
(M)
calculate_imagemagick_features.py:104
↓ 2 callersFunctionrow_normalize
(M)
calculate_glove_features.py:61
↓ 2 callersFunctionrow_normalize
(M)
calculate_w2v_features.py:44
↓ 2 callersFunctionsave_memory
(tokens)
prepare_common_tokens.py:54
↓ 2 callersFunctionsave_memory
(tokens)
prepare_text_tfidf.py:55
↓ 2 callersFunctionsentence_split
(text)
prepare_text_features.py:79
↓ 2 callersFunctiontransform_autocode_report
(text, result={})
prepare_attrs_tfidf.py:22
↓ 2 callersFunctiontranslate_tokens
(sentence)
prepare_text_features.py:130
↓ 2 callersFunctionvalues_cnt
(d)
calculate_misspelling_features.py:55
↓ 2 callersFunctionword_mover_distances
(D)
calculate_w2v_features.py:108
↓ 2 callersFunctionword_mover_distances
(D)
calculate_w2v_wmd_features.py:64
↓ 2 callersFunctionzip_to_int
(zip2)
calculate_chargram_features.py:48
↓ 1 callersFunctionabs_diff
(v1, v2)
calculate_imagehash_features.py:54
↓ 1 callersFunctionabs_diff_features
(df1, df2, result)
calculate_imagemagick_features.py:146
↓ 1 callersFunctionappend_to_csv
(batch, csv_file)
calculate_java-image_features.py:156
↓ 1 callersFunctionbernoulli_mean
(h)
calculate_imagehash_features.py:39
↓ 1 callersFunctioncalc_features
(images1, images2)
calculate_ssim_features.py:64
↓ 1 callersFunctioncalc_features
(images1, images2)
calculate_whash_features.py:54
↓ 1 callersFunctioncalc_features
(images1, images2)
calculate_imagehash_features.py:87
↓ 1 callersFunctioncalc_jaccard
(set1, set2)
calculate_misspelling_features.py:76
↓ 1 callersFunctioncalc_jaccard
(set1, set2, lam=0)
calculate_important_tokens_features.py:51
↓ 1 callersFunctioncalc_jaccard
(set1, set2)
calculate_chargram_features.py:24
↓ 1 callersMethodcalculateFeatures
(Map<String, MBFImage> images1, Map<String, MBFImage> images2)
java-features/src/main/java/ImageFeatures.java:176
↓ 1 callersFunctioncalculate_features
(batch, pool)
mongo_put_iteminfo.py:77
↓ 1 callersFunctionchunck_iterable
(it, n)
calculate_java-image_features.py:17
↓ 1 callersFunctionclean_text
(text)
prepare_text_features.py:73
↓ 1 callersFunctioncompute_chargrams
(batch_size=5000)
prepare_text_features.py:22
↓ 1 callersFunctioncosine
(W1, W2)
calculate_imagemagick_features.py:108
↓ 1 callersFunctioncosine
(W1, W2)
calculate_glove_features.py:76
↓ 1 callersFunctioncosine
(W1, W2)
calculate_w2v_features.py:94
↓ 1 callersFunctioncosine
(c1, c2)
calculate_contact_features.py:26
↓ 1 callersMethodcovertMatchesToPoints
(List<Pair<Keypoint>> matches)
java-features/src/main/java/Utils.java:86
↓ 1 callersFunctioncreate_feature_map
(fmap_filename, features)
model_big_xgb.py:434
↓ 1 callersFunctioncreate_feature_map
(fmap_filename, features)
model_random_xgb.py:445
↓ 1 callersFunctiondict_count_union
(cnt1, cnt2)
calculate_misspelling_features.py:47
↓ 1 callersFunctiondistance_features
(ad1, ad2, result)
calculate_imagemagick_features.py:121
↓ 1 callersFunctiondistmat
(X, C)
calculate_imagemagick_features.py:77
↓ 1 callersFunctiondistmat
(X, C)
calculate_glove_features.py:69
↓ 1 callersFunctiondistmat
(X, C)
calculate_w2v_features.py:58
↓ 1 callersFunctiondistmat
(X, C)
calculate_w2v_wmd_features.py:52
↓ 1 callersFunctionellipse_centroid_features
(df1, df2, result)
calculate_imagemagick_features.py:165
↓ 1 callersMethodextractEmails
(String line)
java-features/src/main/java/ContactDetailExtractor.java:113
↓ 1 callersMethodextractHashTags
(String line)
java-features/src/main/java/ContactDetailExtractor.java:184
↓ 1 callersMethodextractPhones
(String line)
java-features/src/main/java/ContactDetailExtractor.java:132
↓ 1 callersMethodextractPlaceholders
(String line)
java-features/src/main/java/ContactDetailExtractor.java:197
↓ 1 callersFunctionextract_both
(s)
mongo_put_images.py:17
↓ 1 callersFunctionextract_dhash
(img, hash_size=20)
prepare_image_hashes.py:19
↓ 1 callersFunctionextract_features
(line)
calculate_java-image_features.py:53
↓ 1 callersFunctionfile_size
(s)
mongo_put_images.py:71
↓ 1 callersMethodfindImage
(String imageId, boolean fromZip)
java-features/src/main/java/ImageFeatures.java:290
↓ 1 callersFunctionfull_text_features
(c1, c2, row, result)
calculate_glove_features.py:96
↓ 1 callersFunctionfull_text_features
(c1, c2, row, result)
calculate_w2v_features.py:115
↓ 1 callersFunctionfull_text_features
(c1, c2, row, result)
calculate_w2v_wmd_features.py:71
↓ 1 callersFunctiongeometry_match
(df1, df2)
calculate_imagemagick_features.py:69
↓ 1 callersFunctionget_path
(image_id)
calculate_ssim_features.py:20
↓ 1 callersFunctionget_pickled_signatures
()
prepare_image_hashes.py:51
↓ 1 callersFunctionget_pickled_signatures
()
calculate_ssim_features.py:31
↓ 1 callersFunctionget_pickled_signatures
()
calculate_whash_features.py:30
↓ 1 callersFunctionget_pickled_signatures
()
calculate_java-image_features.py:25
↓ 1 callersFunctionget_pickled_whashes
()
calculate_whash_features.py:22
↓ 1 callersFunctionhamming_distance
(h1, h2)
calculate_whash_features.py:45
↓ 1 callersMethodhistogramFeatures
(Map<String, Object> features, Map<String, MBFImage> images1, Map<String, MBFImage> images2)
java-features/src/main/java/ImageFeatures.java:238
↓ 1 callersFunctionis_eng
(s)
prepare_text_features.py:153
↓ 1 callersFunctionis_eng_digit_mixed
(s)
prepare_text_features.py:161
↓ 1 callersFunctionis_rus_digit_mixed
(s)
prepare_text_features.py:156
↓ 1 callersMethoditemPairsData
()
java-features/src/main/java/Utils.java:33
↓ 1 callersMethodloadIds
(File file)
java-features/src/main/java/ImageFeatures.java:337
↓ 1 callersFunctionload_corrections
()
calculate_text_features.py:34
↓ 1 callersFunctionload_json
(collection, filename)
mongo_data.py:17
↓ 1 callersFunctionload_models
()
calculate_text_features.py:81
↓ 1 callersFunctionmanhattan
(W1, W2)
calculate_imagemagick_features.py:84
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