corel16k002

mldr.datasets::get.mldr("corel16k002")

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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	13761
Attributes	664
Inputs	500
Labels	164
Labelsets	4868
Single labelsets	3103
Max frequency	251
Cardinality	2.8824
Density	0.0176
Mean IR	37.6781
SCUMBLE	0.2883
TCS	19.8049

Citation

Barnard, K.; Duygulu, P.; Forsyth, D.; de Freitas, N.; Blei, D. M.; Jordan, M. I. (2003). Matching words and pictures. In Journal of Machine Learning Research, 3(), 1107--1135.

@article{,
    title = "Matching words and pictures",
    author = "Barnard, K. and Duygulu, P. and Forsyth, D. and de Freitas, N. and Blei, D. M. and Jordan, M. I.",
    journal = "Journal of Machine Learning Research",
    year = "2003",
    volume = "3",
    pages = "1107--1135",
}

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 Cluster1 binary Cluster2 binary Cluster3 binary Cluster4 binary Cluster5 binary Cluster6 binary Cluster7 binary Cluster8 binary Cluster9 binary Cluster10 binary Cluster11 binary Cluster12 binary Cluster13 binary Cluster14 binary Cluster15 binary Cluster16 binary Cluster17 binary Cluster18 binary Cluster19 binary Cluster20 binary Cluster21 binary Cluster22 binary Cluster23 binary Cluster24 binary Cluster25 binary Cluster26 binary Cluster27 binary Cluster28 binary Cluster29 binary Cluster30 binary Cluster31 binary Cluster32 binary Cluster33 binary Cluster34 binary Cluster35 binary Cluster36 binary Cluster37 binary Cluster38 binary Cluster39 binary Cluster40 binary Cluster41 binary Cluster42 binary Cluster43 binary Cluster44 binary Cluster45 binary Cluster46 binary Cluster47 binary Cluster48 binary Cluster49 binary Cluster50 binary Cluster51 binary Cluster52 binary Cluster53 binary Cluster54 binary Cluster55 binary Cluster56 binary Cluster57 binary Cluster58 binary Cluster59 binary Cluster60 binary Cluster61 binary Cluster62 binary Cluster63 binary Cluster64 binary Cluster65 binary Cluster66 binary Cluster67 binary Cluster68 binary Cluster69 binary Cluster70 binary Cluster71 binary Cluster72 binary Cluster73 binary Cluster74 binary Cluster75 binary Cluster76 binary Cluster77 binary Cluster78 binary Cluster79 binary Cluster80 binary Cluster81 binary Cluster82 binary Cluster83 binary Cluster84 binary Cluster85 binary Cluster86 binary Cluster87 binary Cluster88 binary Cluster89 binary Cluster90 binary Cluster91 binary Cluster92 binary Cluster93 binary Cluster94 binary Cluster95 binary Cluster96 binary Cluster97 binary Cluster98 binary Cluster99 binary Cluster100 binary Cluster101 binary Cluster102 binary Cluster103 binary Cluster104 binary Cluster105 binary Cluster106 binary Cluster107 binary Cluster108 binary Cluster109 binary Cluster110 binary Cluster111 binary Cluster112 binary Cluster113 binary Cluster114 binary Cluster115 binary Cluster116 binary Cluster117 binary Cluster118 binary Cluster119 binary Cluster120 binary Cluster121 binary Cluster122 binary Cluster123 binary Cluster124 binary Cluster125 binary Cluster126 binary Cluster127 binary Cluster128 binary Cluster129 binary Cluster130 binary Cluster131 binary Cluster132 binary Cluster133 binary Cluster134 binary Cluster135 binary Cluster136 binary Cluster137 binary Cluster138 binary Cluster139 binary Cluster140 binary Cluster141 binary Cluster142 binary Cluster143 binary Cluster144 binary Cluster145 binary Cluster146 binary Cluster147 binary Cluster148 binary Cluster149 binary Cluster150 binary Cluster151 binary Cluster152 binary Cluster153 binary Cluster154 binary Cluster155 binary Cluster156 binary Cluster157 binary Cluster158 binary Cluster159 binary Cluster160 binary Cluster161 binary Cluster162 binary Cluster163 binary Cluster164 binary Cluster165 binary Cluster166 binary Cluster167 binary Cluster168 binary Cluster169 binary Cluster170 binary Cluster171 binary Cluster172 binary Cluster173 binary Cluster174 binary Cluster175 binary Cluster176 binary Cluster177 binary Cluster178 binary Cluster179 binary Cluster180 binary Cluster181 binary Cluster182 binary Cluster183 binary Cluster184 binary Cluster185 binary Cluster186 binary Cluster187 binary Cluster188 binary Cluster189 binary Cluster190 binary Cluster191 binary Cluster192 binary Cluster193 binary Cluster194 binary Cluster195 binary Cluster196 binary Cluster197 binary Cluster198 binary Cluster199 binary Cluster200

(464 more attributes)

animal SCUMBLE 0.3149 background SCUMBLE 0.1677 beach SCUMBLE 0.3669 bear SCUMBLE 0.2487 bengal SCUMBLE 0.496 bighorn SCUMBLE 0.3432 birds SCUMBLE 0.217 boats SCUMBLE 0.3868 bobcat SCUMBLE 0.5007 bottles SCUMBLE 0.0497 branch SCUMBLE 0.2617 branches SCUMBLE 0.4865 bridge SCUMBLE 0.4029 building SCUMBLE 0.3351 bush SCUMBLE 0.4789 butterfly SCUMBLE 0.4202 cactus SCUMBLE 0.3649 canyon SCUMBLE 0.4525 cars SCUMBLE 0.1909 cat SCUMBLE 0.3393 caterpillar SCUMBLE 0.4428 cheetah SCUMBLE 0.566 church SCUMBLE 0.3729 city SCUMBLE 0.3942 cliff SCUMBLE 0.4456 close-up SCUMBLE 0.2286 closeup SCUMBLE 0.173 clouds SCUMBLE 0.2787 coast SCUMBLE 0.4065 coral SCUMBLE 0.1091 costume SCUMBLE 0.5026 courtyard SCUMBLE 0.4947 coyote SCUMBLE 0.5793 crop SCUMBLE 0.3398 crystal SCUMBLE 0.1686 dall SCUMBLE 0.5235 desert SCUMBLE 0.2892 designs SCUMBLE 0.3261 display SCUMBLE 0.2041 diver SCUMBLE 0.1739 dock SCUMBLE 0.5678 door SCUMBLE 0.2835 dunes SCUMBLE 0.5939 eagle SCUMBLE 0.4555 elephant SCUMBLE 0.4602 f-16 SCUMBLE 0.5586 f-18 SCUMBLE 0.5473 fan SCUMBLE 0.3049 farm SCUMBLE 0.5377 feline SCUMBLE 0.4312 fence SCUMBLE 0.3762 field SCUMBLE 0.2495 fish SCUMBLE 0.2457 flowers SCUMBLE 0.1954 foals SCUMBLE 0.2373 food SCUMBLE 0.141 forest SCUMBLE 0.383 formation SCUMBLE 0.5894 fox SCUMBLE 0.3538 fruit SCUMBLE 0.1804 fungus SCUMBLE 0.1277 garden SCUMBLE 0.2433 giraffe SCUMBLE 0.7113 glass SCUMBLE 0.1625 goats SCUMBLE 0.6698 grapes SCUMBLE 0.1668 grass SCUMBLE 0.3226 ground SCUMBLE 0.2342 guard SCUMBLE 0.4626 harbor SCUMBLE 0.6091 hat SCUMBLE 0.3712 head SCUMBLE 0.2158 herd SCUMBLE 0.4752 hills SCUMBLE 0.3449 horizon SCUMBLE 0.4364 horses SCUMBLE 0.2773 hotel SCUMBLE 0.6187 house SCUMBLE 0.3507 ice SCUMBLE 0.2803 insect SCUMBLE 0.2301 island SCUMBLE 0.656 jaguar SCUMBLE 0.6004 jet SCUMBLE 0.3012 landscape SCUMBLE 0.5563 leaf SCUMBLE 0.2714 leaves SCUMBLE 0.1209 leopard SCUMBLE 0.5084 lichen SCUMBLE 0.137 light SCUMBLE 0.2816 lizard SCUMBLE 0.2537 lynx SCUMBLE 0.447 mare SCUMBLE 0.2311 market SCUMBLE 0.3611 military SCUMBLE 0.4906 model SCUMBLE 0.4089 mountain SCUMBLE 0.2666 mushroom SCUMBLE 0.1245 ocean SCUMBLE 0.1127 palace SCUMBLE 0.4076 parade SCUMBLE 0.4874 park SCUMBLE 0.5721 pattern SCUMBLE 0.1867 people SCUMBLE 0.3405 petals SCUMBLE 0.386 pillar SCUMBLE 0.2919 plane SCUMBLE 0.3498 plants SCUMBLE 0.1362 polar SCUMBLE 0.2177 rabbit SCUMBLE 0.5769 reef SCUMBLE 0.212 reflection SCUMBLE 0.476 restaurant SCUMBLE 0.4831 river SCUMBLE 0.5677 road SCUMBLE 0.4299 rock SCUMBLE 0.3056 rodent SCUMBLE 0.6234 ruins SCUMBLE 0.2261 runway SCUMBLE 0.3767 saguaro SCUMBLE 0.4803 sailboats SCUMBLE 0.4839 sails SCUMBLE 0.6207 sand SCUMBLE 0.2948 sea SCUMBLE 0.3153 shadows SCUMBLE 0.3474 sheep SCUMBLE 0.4213 ship SCUMBLE 0.6319 shops SCUMBLE 0.296 shore SCUMBLE 0.4841 signs SCUMBLE 0.3502 sky SCUMBLE 0.3625 skyline SCUMBLE 0.4848 slope SCUMBLE 0.5053 smoke SCUMBLE 0.4632 snake SCUMBLE 0.3444 snow SCUMBLE 0.2379 squirrel SCUMBLE 0.5219 statue SCUMBLE 0.2685 stone SCUMBLE 0.2044 street SCUMBLE 0.3308 sunset SCUMBLE 0.3833 temple SCUMBLE 0.3323 textile SCUMBLE 0.1876 texture SCUMBLE 0.17 tiger SCUMBLE 0.4381 tower SCUMBLE 0.4982 town SCUMBLE 0.5038 tree SCUMBLE 0.3613 trunk SCUMBLE 0.4425 tulip SCUMBLE 0.3746 valley SCUMBLE 0.3749 vegetation SCUMBLE 0.5965 vehicles SCUMBLE 0.4537 village SCUMBLE 0.5738 wall SCUMBLE 0.1976 water SCUMBLE 0.4003 waves SCUMBLE 0.4333 window SCUMBLE 0.2025 wine SCUMBLE 0.1461 wings SCUMBLE 0.4432 wolf SCUMBLE 0.4149 woman SCUMBLE 0.4066 wood SCUMBLE 0.3081 woodland SCUMBLE 0.5065 zebra SCUMBLE 0.604

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