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scikit-learn 1.3.2
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# `sklearn.utils`.as_float_array

sklearn.utils.as_float_array(X, *, copy=True, force_all_finite=True)

  Convert an array-like to an array of floats.

  The new dtype will be np.float32 or np.float64, depending on the original type. The function can create a copy or modify the argument depending on the argument copy.

  Parameters:
    X{array-like, sparse matrix}

      The input data.

    copy bool, default=True

      If True, a copy of X will be created. If False, a copy may still be returned if X’s dtype is not a floating point type.

    force_all_finite bool or ‘allow-nan’, default=True

      Whether to raise an error on np.inf, np.nan, pd.NA in X. The possibilities are:

      - True: Force all values of X to be finite.

      - False: accepts np.inf, np.nan, pd.NA in X.

      - ‘allow-nan’: accepts only np.nan and pd.NA values in X. Values cannot be infinite.

      New in version 0.20: `force_all_finite` accepts the string `'allow-nan'`.

      Changed in version 0.23: Accepts `pd.NA` and converts it into `np.nan`

  Returns:
    XT{ndarray, sparse matrix}

      An array of type float.