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    Class KMeans (0.21.0) 

      KMeans 
 ( 
 n_clusters 
 : 
 int 
 = 
 8 
 )

    K-Means clustering.

    Parameter

    Name
    Description
    n_clusters
    int, default 8

    The number of clusters to form as well as the number of centroids to generate. Default to 8.

    Properties

    cluster_centers_

    Information of cluster centers.

    Returns
    Type
    Description
    bigframes.dataframe.DataFrame
    DataFrame of cluster centers, containing following columns: centroid_id: An integer that identifies the centroid. feature: The column name that contains the feature. numerical_value: If feature is numeric, the value of feature for the centroid that centroid_id identifies. If feature is not numeric, the value is NULL. categorical_value: An list of mappings containing information about categorical features. Each mapping contains the following fields: categorical_value.category: The name of each category. categorical_value.value: The value of categorical_value.category for the centroid that centroid_id identifies. The output contains one row per feature per centroid.

    Methods

    __repr__

      __repr__ 
 ()

    Print the estimator's constructor with all non-default parameter values

    fit

      fit 
 ( 
 X 
 : 
 typing 
 . 
 Union 
 [ 
 bigframes 
 . 
 dataframe 
 . 
 DataFrame 
 , 
 bigframes 
 . 
 series 
 . 
 Series 
 ], 
 y 
 : 
 typing 
 . 
 Optional 
 [ 
 typing 
 . 
 Union 
 [ 
 bigframes 
 . 
 dataframe 
 . 
 DataFrame 
 , 
 bigframes 
 . 
 series 
 . 
 Series 
 ] 
 ] 
 = 
 None 
 , 
 ) 
 - 
> bigframes 
 . 
 ml 
 . 
 base 
 . 
 _T

    Compute k-means clustering.

    Parameters
    Name
    Description
    X
    bigframes.dataframe.DataFrame or bigframes.series.Series

    DataFrame of shape (n_samples, n_features). Training data.

    y
    default None

    Not used, present here for API consistency by convention.

    Returns
    Type
    Description
    KMeans
    Fitted Estimator.

    get_params

      get_params 
 ( 
 deep 
 : 
 bool 
 = 
 True 
 ) 
 - 
> typing 
 . 
 Dict 
 [ 
 str 
 , 
 typing 
 . 
 Any 
 ]

    Get parameters for this estimator.

    Parameter
    Name
    Description
    deep
    bool, default True

    Default True . If True, will return the parameters for this estimator and contained subobjects that are estimators.

    Returns
    Type
    Description
    Dictionary
    A dictionary of parameter names mapped to their values.

    predict

      predict 
 ( 
 X 
 : 
 typing 
 . 
 Union 
 [ 
 bigframes 
 . 
 dataframe 
 . 
 DataFrame 
 , 
 bigframes 
 . 
 series 
 . 
 Series 
 ] 
 ) 
 - 
> bigframes 
 . 
 dataframe 
 . 
 DataFrame

    Predict the closest cluster each sample in X belongs to.

    Parameter
    Name
    Description
    X
    bigframes.dataframe.DataFrame or bigframes.series.Series

    DataFrame of shape (n_samples, n_features). New data to predict.

    Returns
    Type
    Description
    bigframes.dataframe.DataFrame
    DataFrame of shape (n_samples, n_input_columns + n_prediction_columns). Returns predicted labels.

    register

      register 
 ( 
 vertex_ai_model_id 
 : 
 typing 
 . 
 Optional 
 [ 
 str 
 ] 
 = 
 None 
 ) 
 - 
> bigframes 
 . 
 ml 
 . 
 base 
 . 
 _T

    Register the model to Vertex AI.

    After register, go to Google Cloud Console ( https://console.cloud.google.com/vertex-ai/models ) to manage the model registries. Refer to https://cloud.google.com/vertex-ai/docs/model-registry/introduction for more options.

    Parameter
    Name
    Description
    vertex_ai_model_id
    Optional[str], default None

    optional string id as model id in Vertex. If not set, will by default to 'bigframes_{bq_model_id}'. Vertex Ai model id will be truncated to 63 characters due to its limitation.

    score

      score 
 ( 
 X 
 : 
 typing 
 . 
 Union 
 [ 
 bigframes 
 . 
 dataframe 
 . 
 DataFrame 
 , 
 bigframes 
 . 
 series 
 . 
 Series 
 ], 
 y 
 = 
 None 
 ) 
 - 
> bigframes 
 . 
 dataframe 
 . 
 DataFrame

    Calculate evaluation metrics of the model.

    Parameters
    Name
    Description
    X
    bigframes.dataframe.DataFrame or bigframes.series.Series

    DataFrame of shape (n_samples, n_features). New Data.

    y
    default None

    Not used, present here for API consistency by convention.

    Returns
    Type
    Description
    bigframes.dataframe.DataFrame
    DataFrame of the metrics.

    to_gbq

      to_gbq 
 ( 
 model_name 
 : 
 str 
 , 
 replace 
 : 
 bool 
 = 
 False 
 ) 
 - 
> bigframes 
 . 
 ml 
 . 
 cluster 
 . 
 KMeans

    Save the model to BigQuery.

    Parameters
    Name
    Description
    model_name
    str

    the name of the model.

    replace
    bool, default False

    whether to replace if the model already exists. Default to False.

    Returns
    Type
    Description
    KMeans
    saved model.
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