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{
            
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  "access_rights": "",
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  "access_rights": "",
            
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  "author": "Zhen Zhang",
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  "author": "Zhen Zhang",
            
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  "author_email": "",
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  "author_email": "",
            
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  "citation": [
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  "citation": [
            
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    "https://doi.org/10.48550/arXiv.2404.18134",
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    "https://doi.org/10.48550/arXiv.2404.18134",
            
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    "https://doi.org/10.48550/arXiv.2406.03012",
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    "https://doi.org/10.48550/arXiv.2406.03012",
            
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    "https://doi.org/10.48550/arXiv.2311.02757"
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    "https://doi.org/10.48550/arXiv.2311.02757"
            
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  ],
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  ],
            
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
            
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  "defined_in": "https://doi.org/10.48550/arXiv.2404.01356",
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  "defined_in": "https://doi.org/10.48550/arXiv.2404.01356",
            
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  "doi": "10.57702/kizmvro7",
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  "doi": "10.57702/kizmvro7",
            
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  "doi_date_published": null,
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  "doi_date_published": "2024-12-02",
            
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  "doi_publisher": "TIB",
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  "doi_publisher": "TIB",
            
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  "doi_status": false,
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  "doi_status": true,
            
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  "domain": "https://service.tib.eu/ldmservice",
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  "domain": "https://service.tib.eu/ldmservice",
            
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  "groups": [
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  "groups": [
            
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    {
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    {
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Bias in Machine Learning",
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      "display_name": "Bias in Machine Learning",
            
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      "name": "bias-in-machine-learning",
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      "name": "bias-in-machine-learning",
            
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      "title": "Bias in Machine Learning"
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      "title": "Bias in Machine Learning"
            
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    },
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    },
            
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    {
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    {
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Credit",
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      "display_name": "Credit",
            
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      "id": "92b10418-1123-45e6-ac92-66f58986f64b",
            
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      "image_display_url": "",
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      "image_display_url": "",
            
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      "name": "credit",
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      "name": "credit",
            
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      "title": "Credit"
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      "title": "Credit"
            
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    },
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    },
            
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    {
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    {
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Credit Risk",
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      "display_name": "Credit Risk",
            
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      "image_display_url": "",
            
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      "name": "credit-risk",
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      "name": "credit-risk",
            
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      "title": "Credit Risk"
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      "title": "Credit Risk"
            
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    },
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    },
            
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    {
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    {
            
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      "description": "",
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      "description": "",
            
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      "display_name": "Credit risk assessment",
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      "display_name": "Credit risk assessment",
            
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      "id": "5fc4cf30-2fe7-45fe-aa21-2e9d3cce7b4d",
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      "image_display_url": "",
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      "image_display_url": "",
            
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      "name": "credit-risk-assessment",
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      "name": "credit-risk-assessment",
            
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      "title": "Credit risk assessment"
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      "title": "Credit risk assessment"
            
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    }
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    }
            
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  ],
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  ],
            
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  "id": "bca05f94-b4a5-40cb-9643-d18f4b03212f",
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  "id": "bca05f94-b4a5-40cb-9643-d18f4b03212f",
            
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  "isopen": false,
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  "isopen": false,
            
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  "landing_page": "https://doi.org/10.24432/C5NC77",
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  "landing_page": "https://doi.org/10.24432/C5NC77",
            
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  "license_title": null,
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  "license_title": null,
            
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  "link_orkg": "",
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  "link_orkg": "",
            
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  "metadata_created": "2024-12-02T17:52:14.999928",
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  "metadata_created": "2024-12-02T17:52:14.999928",
            
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  "metadata_modified": "2024-12-02T17:52:14.999935",
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  "metadata_modified": "2024-12-02T17:52:15.360565",
            
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  "name": "german-credit",
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  "name": "german-credit",
            
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  "notes": "Each node is a client in a German bank, while each edge 
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  "notes": "Each node is a client in a German bank, while each edge 
            
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between any two clients represents that they bear similar credit 
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between any two clients represents that they bear similar credit 
            
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accounts. Here the gender of bank clients is considered as the 
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accounts. Here the gender of bank clients is considered as the 
            
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sensitive attribute, and the task is to classify the credit risk of 
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sensitive attribute, and the task is to classify the credit risk of 
            
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the clients as high or low.",
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the clients as high or low.",
            
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  "num_tags": 11,
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  "organization": {
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  "organization": {
            
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    "approval_status": "approved",
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    "approval_status": "approved",
            
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    "created": "2024-11-25T12:11:38.292601",
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    "state": "active",
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    "title": "No Organization",
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    "title": "No Organization",
            
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    "type": "organization"
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    "type": "organization"
            
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  "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559",
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  "owner_org": "079d46db-32df-4b48-91f3-0a8bc8f69559",
            
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  "private": false,
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  "private": false,
            
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  "relationships_as_object": [],
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  "relationships_as_object": [],
            
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  "relationships_as_subject": [],
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  "relationships_as_subject": [],
            
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      "created": "2024-12-02T18:38:42",
            
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      "data": [
            
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        "dcterms:title",
            
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      ],
            
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      "description": "The json representation of the dataset with its 
            
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distributions based on DCAT.",
            
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      "format": "JSON",
            
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      "hash": "",
            
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      "id": "169bcc18-bd89-4904-b770-5e69f045cc43",
            
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      "last_modified": "2024-12-02T17:52:15.352813",
            
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      "metadata_modified": "2024-12-02T17:52:15.363311",
            
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      "mimetype": "application/json",
            
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      "name": "Original Metadata",
            
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      "size": 1162,
            
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      "state": "active",
            
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      "url_type": "upload"
            
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    }
            
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  ],
            
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  "state": "active",
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  "state": "active",
            
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  "tags": [
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  "tags": [
            
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    {
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      "display_name": "Bias in Machine Learning",
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      "display_name": "Bias in Machine Learning",
            
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      "name": "Bias in Machine Learning",
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    },
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      "display_name": "Binary Classification",
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      "display_name": "Binary Classification",
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "Credit",
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      "display_name": "Credit",
            
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      "id": "9b2ded5a-b60f-4bbc-ab3c-1848ce641fec",
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      "id": "9b2ded5a-b60f-4bbc-ab3c-1848ce641fec",
            
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      "name": "Credit",
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      "name": "Credit",
            
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      "state": "active",
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      "state": "active",
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "Credit Risk",
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      "display_name": "Credit Risk",
            
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      "id": "fab2c14b-9715-44b5-b5ae-0411ae2c4470",
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      "id": "fab2c14b-9715-44b5-b5ae-0411ae2c4470",
            
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      "name": "Credit Risk",
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      "name": "Credit Risk",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "German Credit",
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      "display_name": "German Credit",
            
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      "id": "30309639-c098-4dcd-aa15-00710850cfb0",
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      "id": "30309639-c098-4dcd-aa15-00710850cfb0",
            
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      "name": "German Credit",
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      "name": "German Credit",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "Lending",
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      "display_name": "Lending",
            
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      "id": "ae9468b0-15c3-4d16-9836-f765a718832a",
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      "id": "ae9468b0-15c3-4d16-9836-f765a718832a",
            
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      "name": "Lending",
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      "name": "Lending",
            
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      "state": "active",
            
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
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      "display_name": "Neural Networks",
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      "display_name": "Neural Networks",
            
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      "name": "Neural Networks",
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      "state": "active",
            
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    },
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    },
            
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      "display_name": "Numerical Attributes",
            
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      "name": "Numerical Attributes",
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      "name": "Numerical Attributes",
            
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      "state": "active",
            
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "banking",
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      "display_name": "banking",
            
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      "id": "80a374f4-ef10-4b35-8453-002c7a12914a",
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      "id": "80a374f4-ef10-4b35-8453-002c7a12914a",
            
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      "name": "banking",
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      "name": "banking",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "credit risk",
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      "display_name": "credit risk",
            
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      "id": "a3a4e2d3-7bf1-4e96-803e-514212869ab5",
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      "id": "a3a4e2d3-7bf1-4e96-803e-514212869ab5",
            
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      "name": "credit risk",
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      "name": "credit risk",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    },
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    },
            
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    {
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    {
            
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      "display_name": "gender",
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      "display_name": "gender",
            
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      "id": "af90adbe-d62d-4309-ba7b-132696a7db64",
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      "id": "af90adbe-d62d-4309-ba7b-132696a7db64",
            
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      "name": "gender",
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      "name": "gender",
            
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      "state": "active",
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      "state": "active",
            
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      "vocabulary_id": null
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      "vocabulary_id": null
            
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    }
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    }
            
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  ],
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  ],
            
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  "title": "German Credit",
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  "title": "German Credit",
            
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  "type": "dataset",
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  "type": "dataset",
            
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  "version": ""
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  "version": ""
            
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}
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}