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Classes
KBinsDiscretizer

KBinsDiscretizer

Bin continuous data into intervals.

Read more in the User Guide.

Python Reference (opens in a new tab)

Constructors

constructor()

Signature

new KBinsDiscretizer(opts?: object): KBinsDiscretizer;

Parameters

NameTypeDescription
opts?object-
opts.dtype?anyThe desired data-type for the output. If undefined, output dtype is consistent with input dtype. Only np.float32 and np.float64 are supported.
opts.encode?"onehot" | "onehot-dense" | "ordinal"Method used to encode the transformed result. Default Value 'onehot'
opts.n_bins?number | ArrayLikeThe number of bins to produce. Raises ValueError if n\_bins < 2. Default Value 5
opts.random_state?numberDetermines random number generation for subsampling. Pass an int for reproducible results across multiple function calls. See the subsample parameter for more details. See Glossary.
opts.strategy?"uniform" | "quantile" | "kmeans"Strategy used to define the widths of the bins. Default Value 'quantile'
opts.subsample?numberMaximum number of samples, used to fit the model, for computational efficiency. Used when strategy="quantile". subsample=None means that all the training samples are used when computing the quantiles that determine the binning thresholds. Since quantile computation relies on sorting each column of X and that sorting has an n log(n) time complexity, it is recommended to use subsampling on datasets with a very large number of samples.

Returns

KBinsDiscretizer

Defined in: generated/preprocessing/KBinsDiscretizer.ts:23 (opens in a new tab)

Properties

_isDisposed

boolean = false

Defined in: generated/preprocessing/KBinsDiscretizer.ts:21 (opens in a new tab)

_isInitialized

boolean = false

Defined in: generated/preprocessing/KBinsDiscretizer.ts:20 (opens in a new tab)

_py

PythonBridge

Defined in: generated/preprocessing/KBinsDiscretizer.ts:19 (opens in a new tab)

id

string

Defined in: generated/preprocessing/KBinsDiscretizer.ts:16 (opens in a new tab)

opts

any

Defined in: generated/preprocessing/KBinsDiscretizer.ts:17 (opens in a new tab)

Accessors

bin_edges_

The edges of each bin. Contain arrays of varying shapes (n\_bins\_, ) Ignored features will have empty arrays.

Signature

bin_edges_(): Promise<any[]>;

Returns

Promise<any[]>

Defined in: generated/preprocessing/KBinsDiscretizer.ts:385 (opens in a new tab)

feature_names_in_

Names of features seen during fit. Defined only when X has feature names that are all strings.

Signature

feature_names_in_(): Promise<ArrayLike>;

Returns

Promise<ArrayLike>

Defined in: generated/preprocessing/KBinsDiscretizer.ts:466 (opens in a new tab)

n_bins_

Number of bins per feature. Bins whose width are too small (i.e., <= 1e-8) are removed with a warning.

Signature

n_bins_(): Promise<ArrayLike>;

Returns

Promise<ArrayLike>

Defined in: generated/preprocessing/KBinsDiscretizer.ts:412 (opens in a new tab)

n_features_in_

Number of features seen during fit.

Signature

n_features_in_(): Promise<number>;

Returns

Promise<number>

Defined in: generated/preprocessing/KBinsDiscretizer.ts:439 (opens in a new tab)

py

Signature

py(): PythonBridge;

Returns

PythonBridge

Defined in: generated/preprocessing/KBinsDiscretizer.ts:64 (opens in a new tab)

Signature

py(pythonBridge: PythonBridge): void;

Parameters

NameType
pythonBridgePythonBridge

Returns

void

Defined in: generated/preprocessing/KBinsDiscretizer.ts:68 (opens in a new tab)

Methods

dispose()

Disposes of the underlying Python resources.

Once dispose() is called, the instance is no longer usable.

Signature

dispose(): Promise<void>;

Returns

Promise<void>

Defined in: generated/preprocessing/KBinsDiscretizer.ts:125 (opens in a new tab)

fit()

Fit the estimator.

Signature

fit(opts: object): Promise<any>;

Parameters

NameTypeDescription
optsobject-
opts.X?ArrayLike[]Data to be discretized.
opts.y?anyIgnored. This parameter exists only for compatibility with Pipeline.

Returns

Promise<any>

Defined in: generated/preprocessing/KBinsDiscretizer.ts:142 (opens in a new tab)

fit_transform()

Fit to data, then transform it.

Fits transformer to X and y with optional parameters fit\_params and returns a transformed version of X.

Signature

fit_transform(opts: object): Promise<any[]>;

Parameters

NameTypeDescription
optsobject-
opts.X?ArrayLike[]Input samples.
opts.fit_params?anyAdditional fit parameters.
opts.y?ArrayLikeTarget values (undefined for unsupervised transformations).

Returns

Promise<any[]>

Defined in: generated/preprocessing/KBinsDiscretizer.ts:184 (opens in a new tab)

get_feature_names_out()

Get output feature names.

Signature

get_feature_names_out(opts: object): Promise<any>;

Parameters

NameTypeDescription
optsobject-
opts.input_features?anyInput features.

Returns

Promise<any>

Defined in: generated/preprocessing/KBinsDiscretizer.ts:235 (opens in a new tab)

init()

Initializes the underlying Python resources.

This instance is not usable until the Promise returned by init() resolves.

Signature

init(py: PythonBridge): Promise<void>;

Parameters

NameType
pyPythonBridge

Returns

Promise<void>

Defined in: generated/preprocessing/KBinsDiscretizer.ts:77 (opens in a new tab)

inverse_transform()

Transform discretized data back to original feature space.

Note that this function does not regenerate the original data due to discretization rounding.

Signature

inverse_transform(opts: object): Promise<ArrayLike>;

Parameters

NameTypeDescription
optsobject-
opts.Xt?ArrayLike[]Transformed data in the binned space.

Returns

Promise<ArrayLike>

Defined in: generated/preprocessing/KBinsDiscretizer.ts:275 (opens in a new tab)

set_output()

Set output container.

See Introducing the set_output API for an example on how to use the API.

Signature

set_output(opts: object): Promise<any>;

Parameters

NameTypeDescription
optsobject-
opts.transform?"default" | "pandas"Configure output of transform and fit\_transform.

Returns

Promise<any>

Defined in: generated/preprocessing/KBinsDiscretizer.ts:315 (opens in a new tab)

transform()

Discretize the data.

Signature

transform(opts: object): Promise<ArrayLike>;

Parameters

NameTypeDescription
optsobject-
opts.X?ArrayLike[]Data to be discretized.

Returns

Promise<ArrayLike>

Defined in: generated/preprocessing/KBinsDiscretizer.ts:350 (opens in a new tab)