corel16k008

mldr.datasets::get.mldr("corel16k008")

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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	13864
Attributes	668
Inputs	500
Labels	168
Labelsets	4956
Single labelsets	3169
Max frequency	253
Cardinality	2.883
Density	0.0172
Mean IR	36.2
SCUMBLE	0.2894
TCS	19.8469

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

(468 more attributes)

antlers SCUMBLE 0.5211 baby SCUMBLE 0.3169 background SCUMBLE 0.1694 beach SCUMBLE 0.3745 bears SCUMBLE 0.3485 beetle SCUMBLE 0.4215 bighorn SCUMBLE 0.3504 birds SCUMBLE 0.3084 black SCUMBLE 0.4375 boats SCUMBLE 0.3972 bottles SCUMBLE 0.0644 branch SCUMBLE 0.236 branches SCUMBLE 0.4746 bridge SCUMBLE 0.4013 buildings SCUMBLE 0.3362 bulls SCUMBLE 0.4715 bushes SCUMBLE 0.5191 butterfly SCUMBLE 0.4125 cactus SCUMBLE 0.3176 cars SCUMBLE 0.2024 castle SCUMBLE 0.5019 cat SCUMBLE 0.2123 church SCUMBLE 0.38 city SCUMBLE 0.3885 cliff SCUMBLE 0.4651 close-up SCUMBLE 0.2153 closeup SCUMBLE 0.1681 clouds SCUMBLE 0.2866 coral SCUMBLE 0.0709 costume SCUMBLE 0.5113 courtyard SCUMBLE 0.4801 crop SCUMBLE 0.331 crystal SCUMBLE 0.1674 cubs SCUMBLE 0.3526 dall SCUMBLE 0.518 deer SCUMBLE 0.4609 desert SCUMBLE 0.2733 dock SCUMBLE 0.5685 dog SCUMBLE 0.4772 doors SCUMBLE 0.2846 eagle SCUMBLE 0.4568 elephant SCUMBLE 0.4624 elk SCUMBLE 0.5572 face SCUMBLE 0.231 fence SCUMBLE 0.3754 field SCUMBLE 0.2841 fish SCUMBLE 0.2353 flag SCUMBLE 0.4199 flight SCUMBLE 0.5069 flowers SCUMBLE 0.2063 foal SCUMBLE 0.2373 food SCUMBLE 0.1413 forest SCUMBLE 0.3152 formation SCUMBLE 0.5944 fruit SCUMBLE 0.1847 fungus SCUMBLE 0.1344 gardens SCUMBLE 0.2447 glass SCUMBLE 0.1644 grapes SCUMBLE 0.1668 grass SCUMBLE 0.3035 grizzly SCUMBLE 0.5733 ground SCUMBLE 0.171 guns SCUMBLE 0.524 harbor SCUMBLE 0.612 hats SCUMBLE 0.3963 head SCUMBLE 0.1932 herd SCUMBLE 0.4854 hills SCUMBLE 0.3399 horizon SCUMBLE 0.4343 horns SCUMBLE 0.5636 horses SCUMBLE 0.2587 hotel SCUMBLE 0.6301 house SCUMBLE 0.3515 hunter SCUMBLE 0.5407 hut SCUMBLE 0.719 ice SCUMBLE 0.3193 iceburg SCUMBLE 0.5908 insect SCUMBLE 0.2353 island SCUMBLE 0.6678 jet SCUMBLE 0.2208 kitten SCUMBLE 0.4463 lake SCUMBLE 0.6726 landscape SCUMBLE 0.5583 leaf SCUMBLE 0.2724 leaves SCUMBLE 0.1239 lichen SCUMBLE 0.14 light SCUMBLE 0.2691 lion SCUMBLE 0.33 lizard SCUMBLE 0.2335 locomotive SCUMBLE 0.3043 log SCUMBLE 0.2698 mane SCUMBLE 0.3151 mare SCUMBLE 0.2311 market SCUMBLE 0.361 moss SCUMBLE 0.4233 mountain SCUMBLE 0.2488 museum SCUMBLE 0.5417 mushrooms SCUMBLE 0.1293 nest SCUMBLE 0.3807 night SCUMBLE 0.2413 ocean SCUMBLE 0.0778 palace SCUMBLE 0.4215 park SCUMBLE 0.5743 patterns SCUMBLE 0.1802 penguin SCUMBLE 0.4975 people SCUMBLE 0.3548 petals SCUMBLE 0.4018 plane SCUMBLE 0.2306 plants SCUMBLE 0.1447 polar SCUMBLE 0.2646 railroad SCUMBLE 0.3164 reefs SCUMBLE 0.1992 reflection SCUMBLE 0.4822 reptile SCUMBLE 0.2779 restaurant SCUMBLE 0.4647 river SCUMBLE 0.5724 road SCUMBLE 0.4304 rocks SCUMBLE 0.2694 roof SCUMBLE 0.5652 runway SCUMBLE 0.3729 sailboats SCUMBLE 0.4892 sails SCUMBLE 0.6222 sand SCUMBLE 0.2717 sculpture SCUMBLE 0.2562 sea SCUMBLE 0.2577 sheep SCUMBLE 0.4249 ship SCUMBLE 0.6275 shop SCUMBLE 0.2956 shore SCUMBLE 0.4846 shrine SCUMBLE 0.5873 sign SCUMBLE 0.3499 sky SCUMBLE 0.372 skyline SCUMBLE 0.4786 slope SCUMBLE 0.527 smoke SCUMBLE 0.3896 snake SCUMBLE 0.3191 snow SCUMBLE 0.2575 statue SCUMBLE 0.283 stem SCUMBLE 0.5263 stone SCUMBLE 0.2072 street SCUMBLE 0.3439 sun SCUMBLE 0.3972 sunset SCUMBLE 0.3784 tables SCUMBLE 0.2532 temple SCUMBLE 0.3459 textile SCUMBLE 0.185 texture SCUMBLE 0.17 tower SCUMBLE 0.5012 town SCUMBLE 0.5089 tracks SCUMBLE 0.1279 train SCUMBLE 0.3488 tree SCUMBLE 0.3637 trunk SCUMBLE 0.4404 tulip SCUMBLE 0.3873 tundra SCUMBLE 0.4298 vegetables SCUMBLE 0.0904 vehicles SCUMBLE 0.4493 vineyard SCUMBLE 0.6004 walls SCUMBLE 0.1965 water SCUMBLE 0.4084 waves SCUMBLE 0.4543 white-tailed SCUMBLE 0.5691 windows SCUMBLE 0.2089 wine SCUMBLE 0.1371 wings SCUMBLE 0.4422 wolf SCUMBLE 0.4152 woman SCUMBLE 0.37 wood SCUMBLE 0.3047

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