Missing keyword 'between' for boundary annotation

[Aclrian]

URL Hash

#/sklearn/sklearn.cluster._mean_shift/estimate_bandwidth/quantile

Expected Annotation Type

@boundary

Expected Annotation Inputs

[0, 1]

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Minimal API Data for `sklearn/sklearn.cluster._mean_shift/estimate_bandwidth/quantile`

{
    "schemaVersion": 1,
    "distribution": "scikit-learn",
    "package": "sklearn",
    "version": "1.1.1",
    "modules": [
        {
            "id": "sklearn/sklearn.cluster",
            "name": "sklearn.cluster",
            "imports": [],
            "from_imports": [
                {
                    "module": "sklearn.cluster._affinity_propagation",
                    "declaration": "affinity_propagation",
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                },
                {
                    "module": "sklearn.cluster._affinity_propagation",
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                    "module": "sklearn.cluster._agglomerative",
                    "declaration": "AgglomerativeClustering",
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                    "declaration": "FeatureAgglomeration",
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                    "module": "sklearn.cluster._dbscan",
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                {
                    "module": "sklearn.cluster._kmeans",
                    "declaration": "MiniBatchKMeans",
                    "alias": null
                },
                {
                    "module": "sklearn.cluster._mean_shift",
                    "declaration": "estimate_bandwidth",
                    "alias": null
                },
                {
                    "module": "sklearn.cluster._mean_shift",
                    "declaration": "get_bin_seeds",
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                {
                    "module": "sklearn.cluster._mean_shift",
                    "declaration": "mean_shift",
                    "alias": null
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                    "module": "sklearn.cluster._mean_shift",
                    "declaration": "MeanShift",
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                },
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                    "module": "sklearn.cluster._optics",
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                },
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                    "module": "sklearn.cluster._optics",
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                },
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                    "module": "sklearn.cluster._optics",
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                },
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                },
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                    "module": "sklearn.cluster._spectral",
                    "declaration": "SpectralClustering",
                    "alias": null
                }
            ],
            "classes": [],
            "functions": [
                "sklearn/sklearn.cluster._mean_shift/estimate_bandwidth"
            ]
        }
    ],
    "classes": [],
    "functions": [
        {
            "id": "sklearn/sklearn.cluster._mean_shift/estimate_bandwidth",
            "name": "estimate_bandwidth",
            "qname": "sklearn.cluster._mean_shift.estimate_bandwidth",
            "decorators": [],
            "parameters": [
                {
                    "id": "sklearn/sklearn.cluster._mean_shift/estimate_bandwidth/quantile",
                    "name": "quantile",
                    "qname": "sklearn.cluster._mean_shift.estimate_bandwidth.quantile",
                    "default_value": "0.3",
                    "assigned_by": "NAME_ONLY",
                    "is_public": true,
                    "docstring": {
                        "type": "float, default=0.3",
                        "description": "Should be between [0, 1]\n0.5 means that the median of all pairwise distances is used."
                    },
                    "type": {}
                }
            ],
            "results": [],
            "is_public": true,
            "reexported_by": [
                "sklearn/sklearn.cluster"
            ],
            "description": "Estimate the bandwidth to use with the mean-shift algorithm.\n\nThat this function takes time at least quadratic in n_samples. For large\ndatasets, it's wise to set that parameter to a small value.",
            "docstring": "Estimate the bandwidth to use with the mean-shift algorithm.\n\n    That this function takes time at least quadratic in n_samples. For large\n    datasets, it's wise to set that parameter to a small value.\n\n    Parameters\n    ----------\n    X : array-like of shape (n_samples, n_features)\n        Input points.\n\n    quantile : float, default=0.3\n        Should be between [0, 1]\n        0.5 means that the median of all pairwise distances is used.\n\n    n_samples : int, default=None\n        The number of samples to use. If not given, all samples are used.\n\n    random_state : int, RandomState instance, default=None\n        The generator used to randomly select the samples from input points\n        for bandwidth estimation. Use an int to make the randomness\n        deterministic.\n        See :term:`Glossary <random_state>`.\n\n    n_jobs : int, default=None\n        The number of parallel jobs to run for neighbors search.\n        ``None`` means 1 unless in a :obj:`joblib.parallel_backend` context.\n        ``-1`` means using all processors. See :term:`Glossary <n_jobs>`\n        for more details.\n\n    Returns\n    -------\n    bandwidth : float\n        The bandwidth parameter.\n    "
        }
    ]
}

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Minimal Usage Store for `sklearn/sklearn.cluster._mean_shift/estimate_bandwidth/quantile`

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            "0.1": 1,
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            "0.001": 1
        }
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}

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Additional Context (optional)

Documentation: Should be between [0, 1] 0.5 means that the median of all pairwise distances is used.

At #/sklearn/sklearn.cluster._optics/OPTICS/__init__/xi is the same problem.

[nvollroth]

#/sklearn/sklearn.linear_model._ridge/Ridge/__init__/alpha
It should for the key word 'in i.e.', too.