Yelp - Cometa

Yelp

mldr.datasets::get.mldr("Yelp")

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Full dataset

MULAN/MEKA (.arff) MULAN (.xml) LibSVM KEEL mldr

Partitions: select your desired partitioning strategy, validation and format

	Random	Stratified	Iterative stratified
Hold out	MULAN MEKA LibSVM KEEL mldr	MULAN MEKA LibSVM KEEL mldr	MULAN MEKA LibSVM KEEL mldr
2x5-fold cross validation	MULAN MEKA LibSVM KEEL mldr	MULAN MEKA LibSVM KEEL mldr	MULAN MEKA LibSVM KEEL mldr
10-fold cross validation	MULAN MEKA LibSVM KEEL mldr	MULAN MEKA LibSVM KEEL mldr	MULAN MEKA LibSVM KEEL mldr

Summary

Instances	10806
Attributes	676
Inputs	671
Labels	5
Labelsets	32
Single labelsets	0
Max frequency	2120
Cardinality	1.6383
Density	0.3277
Mean IR	2.8756
SCUMBLE	0.0332
TCS	11.5839

Citation

Hitesh Sajnani, Vaibhav Saini, Kusum Kumar , Eugenia Gabrielova , Pramit Choudary, Cristina Lopes (2013). The Yelp dataset challenge - Multilabel classification of Yelp reviews into relevant categories.

@online{,
  title={The Yelp dataset challenge - Multilabel classification of Yelp reviews into relevant categories},
  author={Hitesh Sajnani, Vaibhav Saini, Kusum Kumar , Eugenia Gabrielova , Pramit Choudary, Cristina Lopes},
  year={2013},
  url={https://www.ics.uci.edu/~vpsaini/}
}

Concurrence plot

In this concurrence plot, sectors represent labels and links between them depict label co-occurrences. SCUMBLE is a measure designed to assess the concurrence among imbalanced labels.

Attributes

all attributes labels

binary back_try binary not_good binary i_have_to binary about_place binary portions binary come_back binary the_food binary that_it_was binary really_like binary food_just binary you_want_to binary to_try_the binary good_thing binary ingredients binary goat_cheese binary ice_cream binary the_service_is binary food_very binary very_cool binary not_just binary felt binary hour_menu binary there_was_a binary i_like_the binary friends binary potato binary the_prices_are binary prices_very binary and_i_have binary cooked binary portion binary thai_food binary go_wrong binary time binary fresh binary bring binary it_was_the binary a_side_of binary chicken binary fine binary find binary staff binary busy binary menu binary much_better binary enough binary only binary going binary pretty binary rice binary feel_like binary plate binary can_say binary total_wine binary stop binary appetizer binary good_prices binary they_have_a binary no_one binary chips binary place_go binary is_one_of binary prime binary bar binary back_again binary bad binary stuff binary grilled binary steak binary fair binary yes binary best binary glass_wine binary great_food binary lots binary not_even binary outside binary i_am_not binary prime_rib binary a_couple_of binary affordable binary come binary kitchen binary last binary restaurant binary service_great binary and_i_had binary last_night binary in_the_area binary just_like binary whole binary liked binary point binary sweet binary i_love_the binary top_notch binary happy_hour binary very_tasty binary table binary expensive binary was_a_little binary beef binary decent binary three binary happy_hours binary treat binary i_had_to binary bbq binary sat_down binary it_would_be binary spring_rolls binary cream_cheese binary not_sure binary happy_hour_is binary priced binary pulled_pork binary coming_back binary try_out binary dining_experience binary attentive binary i_was_in binary pleasantly_surprised binary quite_good binary look binary half_price binary bill binary like_place binary value binary will binary cant_beat binary fun binary really_cool binary wait_staff binary staff_friendly binary sushi binary old_town binary cant binary brought_out binary decor binary several_times binary make binary bowl binary sliders binary first_visit binary way_too binary also_ordered binary party binary several binary mexican_food binary this_is_the binary week binary one_best binary daily_specials binary drink binary we_had_a binary next_door binary hole_wall binary arrived binary quality_food binary they_also_have binary a_bit_of binary strip_mall binary butter binary no binary well binary came_out binary burgers binary without binary looks_like binary left binary less binary money binary very_good binary not binary but_it_was binary is_a_great binary flavor binary yet binary tables binary generous binary not_too binary seems binary one_of_my binary the_place_was binary location binary definitely_worth binary gave binary real binary dont_want binary around binary good_not binary big binary couple binary game binary know binary outdoor_seating binary bit binary disappointed binary meat binary i_am_a

(476 more attributes)

IsFoodGood SCUMBLE 0.0466 IsServiceGood SCUMBLE 0.0462 IsAmbianceGood SCUMBLE 0.0308 IsDealsGood SCUMBLE 0.2074 IsPriceGood SCUMBLE 0.0701

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