PASS is a large-scale image dataset that does not include any humans and which can be used for high-quality pretraining while significantly reducing privacy concerns. Upload by OpenML team.
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1439588 instances - 7 features - 94137 classes - 1775490 missing values
A copy of PLK_Mini dataset from Meta album Set0
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3440 instances - 3 features - 86 classes - 3440 missing values
A copy of MD_MIX_Mini dataset from Meta album Set0
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28240 instances - 69 features - 706 classes - 665053 missing values
A test copy of PCAM dataset from kaggle(Do not use this version)
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220025 instances - 2 features - 0 classes - 0 missing values
No data.
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7349 instances - 49153 features - 37 classes - 0 missing values
No data.
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7349 instances - 49153 features - 37 classes - 0 missing values
No data.
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16000 instances - 27649 features - 2 classes - 0 missing values
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16000 instances - 27649 features - 2 classes - 0 missing values
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4000 instances - 27649 features - 2 classes - 0 missing values
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1000 instances - 27649 features - 2 classes - 0 missing values
Subset of KITS dataset with 100 images and nominal target
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100 instances - 27649 features - 2 classes - 0 missing values
Subset of KITS dataset with 100 images
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100 instances - 27649 features - 0 classes - 0 missing values
Subset of KITS dataset with 100 images
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100 instances - 27649 features - 2 classes - 0 missing values
Subset of KITS dataset with 100 images
0 runs0 likes0 downloads0 reach0 impact
100 instances - 27649 features - 0 classes - 0 missing values