File size: 7,009 Bytes
9a647d3 7fb1d50 9a647d3 7fb1d50 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 |
---
tags:
- bertopic
library_name: bertopic
pipeline_tag: text-classification
license: mit
datasets:
- blbooksgenre
language:
- en
---
# blbooksgenre_topics
This is a [BERTopic](https://github.com/MaartenGr/BERTopic) model.
BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets.
## Usage
To use this model, please install BERTopic:
```
pip install -U bertopic
```
You can use the model as follows:
```python
from bertopic import BERTopic
topic_model = BERTopic.load("davanstrien/blbooksgenre_topics")
topic_model.get_topic_info()
```
## Topic overview
* Number of topics: 57
* Number of training documents: 43752
<details>
<summary>Click here for an overview of all topics.</summary>
| Topic ID | Topic Keywords | Topic Frequency | Label |
|----------|----------------|-----------------|-------|
| -1 | poems - novel - poem - prose - book | 11 | -1_poems_novel_poem_prose |
| 0 | poems - poem - poetry - poets - poetical | 18624 | 0_poems_poem_poetry_poets |
| 1 | novel - author - poem - heir - tales | 4698 | 1_novel_author_poem_heir |
| 2 | ireland - dublin - scotland - irish - edinburgh | 3576 | 2_ireland_dublin_scotland_irish |
| 3 | geography - geographical - maps - map - history | 3104 | 3_geography_geographical_maps_map |
| 4 | shakespeare - acts - prose - comedy - theatre | 1377 | 4_shakespeare_acts_prose_comedy |
| 5 | county - counties - pennsylvania - hampshire - history | 1089 | 5_county_counties_pennsylvania_hampshire |
| 6 | france - spain - europe - pyrenees - paris | 990 | 6_france_spain_europe_pyrenees |
| 7 | sailing - nautical - maritime - boat - voyages | 986 | 7_sailing_nautical_maritime_boat |
| 8 | antiquity - greeks - rome - romans - greece | 744 | 8_antiquity_greeks_rome_romans |
| 9 | illustrations - drawings - pencil - drawn - sketches | 631 | 9_illustrations_drawings_pencil_drawn |
| 10 | africa - transvaal - cape - zululand - african | 610 | 10_africa_transvaal_cape_zululand |
| 11 | egypt - egyptians - cairo - sinai - egyptian | 610 | 11_egypt_egyptians_cairo_sinai |
| 12 | england - britain - british - george - english | 570 | 12_england_britain_british_george |
| 13 | california - alaska - regions - tour - states | 546 | 13_california_alaska_regions_tour |
| 14 | italia - italy - sicily - italian - italians | 491 | 14_italia_italy_sicily_italian |
| 15 | crimean - crimea - turkey - turks - russia | 481 | 15_crimean_crimea_turkey_turks |
| 16 | mexico - rio - honduras - colombia - panama | 433 | 16_mexico_rio_honduras_colombia |
| 17 | wales - maoriland - otago - zealand - auckland | 423 | 17_wales_maoriland_otago_zealand |
| 18 | waterloo - poem - battle - napoleon - battles | 405 | 18_waterloo_poem_battle_napoleon |
| 19 | mining - mineralogy - minerals - metallurgy - metals | 396 | 19_mining_mineralogy_minerals_metallurgy |
| 20 | history - america - states - historical - american | 377 | 20_history_america_states_historical |
| 21 | geology - geological - geologists - cambrian - fossils | 305 | 21_geology_geological_geologists_cambrian |
| 22 | quebec - scotia - canadas - ontario - province | 204 | 22_quebec_scotia_canadas_ontario |
| 23 | rambles - ramble - south - lands - scrambles | 194 | 23_rambles_ramble_south_lands |
| 24 | edition - second - series - third - revised | 159 | 24_edition_second_series_third |
| 25 | rudge - barnaby - hutton - rivers - osborne | 149 | 25_rudge_barnaby_hutton_rivers |
| 26 | memorials - anniversary - memorial - london - address | 134 | 26_memorials_anniversary_memorial_london |
| 27 | railway - railways - railroad - railroads - railroadiana | 115 | 27_railway_railways_railroad_railroads |
| 28 | forest - foresters - woods - trees - forestalled | 112 | 28_forest_foresters_woods_trees |
| 29 | philosophy - humanity - philosophie - moralities - conscience | 97 | 29_philosophy_humanity_philosophie_moralities |
| 30 | gazetteer - geography - geographical - dictionary - topographical | 96 | 30_gazetteer_geography_geographical_dictionary |
| 31 | goldsmith - goldsmiths - novel - writings - epistle | 93 | 31_goldsmith_goldsmiths_novel_writings |
| 32 | regulations - members - committees - rules - committee | 89 | 32_regulations_members_committees_rules |
| 33 | odes - poems - poem - ode - hymno | 87 | 33_odes_poems_poem_ode |
| 34 | doctor - doctors - physician - patients - physicians | 79 | 34_doctor_doctors_physician_patients |
| 35 | geography - schools - longmans - colleges - school | 77 | 35_geography_schools_longmans_colleges |
| 36 | juan - juana - sequel - carlos - genista | 63 | 36_juan_juana_sequel_carlos |
| 37 | sporting - sports - sport - sportsmans - rugby | 56 | 37_sporting_sports_sport_sportsmans |
| 38 | detective - detectives - crime - policeman - city | 52 | 38_detective_detectives_crime_policeman |
| 39 | blanc - mont - blanche - montserrat - montacute | 47 | 39_blanc_mont_blanche_montserrat |
| 40 | jack - jacks - jackdaw - house - author | 46 | 40_jack_jacks_jackdaw_house |
| 41 | dutch - netherlands - holland - dutchman - dutchesse | 43 | 41_dutch_netherlands_holland_dutchman |
| 42 | spider - spiders - adventure - web - webs | 35 | 42_spider_spiders_adventure_web |
| 43 | madrasiana - madras - malabar - mysore - district | 31 | 43_madrasiana_madras_malabar_mysore |
| 44 | doncaster - 1835 - gazette - 1862 - 1868 | 31 | 44_doncaster_1835_gazette_1862 |
| 45 | lays - lay - land - empire - sea | 28 | 45_lays_lay_land_empire |
| 46 | cyprus - syria - palestine - island - asia | 28 | 46_cyprus_syria_palestine_island |
| 47 | gipsies - gipsy - snakes - encyclopaedia - bunyan | 20 | 47_gipsies_gipsy_snakes_encyclopaedia |
| 48 | abydos - bride - turkish - marriage - euphrosyne | 18 | 48_abydos_bride_turkish_marriage |
| 49 | derby - castleton - buxton - matlock - nottingham | 16 | 49_derby_castleton_buxton_matlock |
| 50 | corsair - tale - carlo - mystery - monte | 16 | 50_corsair_tale_carlo_mystery |
| 51 | bushman - bushranger - bushrangers - australian - novel | 13 | 51_bushman_bushranger_bushrangers_australian |
| 52 | months - italy - weeks - six - france | 12 | 52_months_italy_weeks_six |
| 53 | kitty - kittys - catspaw - catriona - father | 12 | 53_kitty_kittys_catspaw_catriona |
| 54 | lighthouses - lighthouse - beacons - lights - lighting | 12 | 54_lighthouses_lighthouse_beacons_lights |
| 55 | balfour - kidnapped - balfouriana - memoirs - adventures | 11 | 55_balfour_kidnapped_balfouriana_memoirs |
</details>
## Training hyperparameters
* calculate_probabilities: False
* language: english
* low_memory: False
* min_topic_size: 10
* n_gram_range: (1, 1)
* nr_topics: 57
* seed_topic_list: None
* top_n_words: 10
* verbose: True
## Framework versions
* Numpy: 1.22.4
* HDBSCAN: 0.8.29
* UMAP: 0.5.3
* Pandas: 1.5.3
* Scikit-Learn: 1.2.2
* Sentence-transformers: 2.2.2
* Transformers: 4.29.2
* Numba: 0.56.4
* Plotly: 5.13.1
* Python: 3.10.11 |