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--- |
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task_categories: |
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- image-classification |
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--- |
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# AutoTrain Dataset for project: cancer-lakera |
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## Dataset Description |
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This dataset has been automatically processed by AutoTrain for project cancer-lakera. |
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### Languages |
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The BCP-47 code for the dataset's language is unk. |
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## Dataset Structure |
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### Data Instances |
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A sample from this dataset looks as follows: |
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```json |
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[ |
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{ |
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"image": "<600x450 RGB PIL image>", |
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"feat_image_id": "ISIC_0024329", |
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"feat_lesion_id": "HAM_0002954", |
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"target": 0, |
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"feat_dx_type": "histo", |
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"feat_age": 75.0, |
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"feat_sex": "female", |
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"feat_localization": "lower extremity" |
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}, |
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{ |
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"image": "<600x450 RGB PIL image>", |
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"feat_image_id": "ISIC_0024372", |
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"feat_lesion_id": "HAM_0005389", |
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"target": 0, |
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"feat_dx_type": "histo", |
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"feat_age": 70.0, |
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"feat_sex": "male", |
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"feat_localization": "lower extremity" |
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} |
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] |
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``` |
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### Dataset Fields |
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The dataset has the following fields (also called "features"): |
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```json |
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{ |
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"image": "Image(decode=True, id=None)", |
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"feat_image_id": "Value(dtype='string', id=None)", |
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"feat_lesion_id": "Value(dtype='string', id=None)", |
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"target": "ClassLabel(names=['actinic_keratoses', 'basal_cell_carcinoma', 'benign_keratosis-like_lesions'], id=None)", |
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"feat_dx_type": "Value(dtype='string', id=None)", |
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"feat_age": "Value(dtype='float64', id=None)", |
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"feat_sex": "Value(dtype='string', id=None)", |
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"feat_localization": "Value(dtype='string', id=None)" |
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} |
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``` |
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### Dataset Splits |
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This dataset is split into a train and validation split. The split sizes are as follow: |
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| Split name | Num samples | |
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| ------------ | ------------------- | |
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| train | 1200 | |
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| valid | 150 | |
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