DescribeEvaluationsInput ¶

class DescribeEvaluationsInput(TypedDict, closed=True):
    filter_variable: NotRequired[
        "capo_machine_learning.types.evaluation_filter_variable.EvaluationFilterVariable"
    ]
    """<p>Use one of the following variable to filter a list of <code>Evaluation</code> objects:</p> <ul> <li> <p> <code>CreatedAt</code> - Sets the search criteria to the <code>Evaluation</code> creation date.</p> </li> <li> <p> <code>Status</code> - Sets the search criteria to the <code>Evaluation</code> status.</p> </li> <li> <p> <code>Name</code> - Sets the search criteria to the contents of <code>Evaluation</code> <b> </b> <code>Name</code>.</p> </li> <li> <p> <code>IAMUser</code> - Sets the search criteria to the user account that invoked an <code>Evaluation</code>.</p> </li> <li> <p> <code>MLModelId</code> - Sets the search criteria to the <code>MLModel</code> that was evaluated.</p> </li> <li> <p> <code>DataSourceId</code> - Sets the search criteria to the <code>DataSource</code> used in <code>Evaluation</code>.</p> </li> <li> <p> <code>DataUri</code> - Sets the search criteria to the data file(s) used in <code>Evaluation</code>. The URL can identify either a file or an Amazon Simple Storage Solution (Amazon S3) bucket or directory.</p> </li> </ul>"""
    eq: NotRequired["capo_machine_learning.types.comparator_value.ComparatorValue"]
    """<p>The equal to operator. The <code>Evaluation</code> results will have <code>FilterVariable</code> values that exactly match the value specified with <code>EQ</code>.</p>"""
    gt: NotRequired["capo_machine_learning.types.comparator_value.ComparatorValue"]
    """<p>The greater than operator. The <code>Evaluation</code> results will have <code>FilterVariable</code> values that are greater than the value specified with <code>GT</code>.</p>"""
    lt: NotRequired["capo_machine_learning.types.comparator_value.ComparatorValue"]
    """<p>The less than operator. The <code>Evaluation</code> results will have <code>FilterVariable</code> values that are less than the value specified with <code>LT</code>.</p>"""
    ge: NotRequired["capo_machine_learning.types.comparator_value.ComparatorValue"]
    """<p>The greater than or equal to operator. The <code>Evaluation</code> results will have <code>FilterVariable</code> values that are greater than or equal to the value specified with <code>GE</code>. </p>"""
    le: NotRequired["capo_machine_learning.types.comparator_value.ComparatorValue"]
    """<p>The less than or equal to operator. The <code>Evaluation</code> results will have <code>FilterVariable</code> values that are less than or equal to the value specified with <code>LE</code>.</p>"""
    ne: NotRequired["capo_machine_learning.types.comparator_value.ComparatorValue"]
    """<p>The not equal to operator. The <code>Evaluation</code> results will have <code>FilterVariable</code> values not equal to the value specified with <code>NE</code>.</p>"""
    prefix: NotRequired["capo_machine_learning.types.comparator_value.ComparatorValue"]
    """<p>A string that is found at the beginning of a variable, such as <code>Name</code> or <code>Id</code>.</p> <p>For example, an <code>Evaluation</code> could have the <code>Name</code> <code>2014-09-09-HolidayGiftMailer</code>. To search for this <code>Evaluation</code>, select <code>Name</code> for the <code>FilterVariable</code> and any of the following strings for the <code>Prefix</code>: </p> <ul> <li> <p>2014-09</p> </li> <li> <p>2014-09-09</p> </li> <li> <p>2014-09-09-Holiday</p> </li> </ul>"""
    sort_order: NotRequired["capo_machine_learning.types.sort_order.SortOrder"]
    """<p>A two-value parameter that determines the sequence of the resulting list of <code>Evaluation</code>.</p> <ul> <li> <p> <code>asc</code> - Arranges the list in ascending order (A-Z, 0-9).</p> </li> <li> <p> <code>dsc</code> - Arranges the list in descending order (Z-A, 9-0).</p> </li> </ul> <p>Results are sorted by <code>FilterVariable</code>.</p>"""
    next_token: NotRequired["capo_machine_learning.types.string_type.StringType"]
    """<p>The ID of the page in the paginated results.</p>"""
    limit: NotRequired["capo_machine_learning.types.page_limit.PageLimit"]
    """<p> The maximum number of <code>Evaluation</code> to include in the result.</p>"""