sklearn.utils.extmath
.weighted_mode¶

sklearn.utils.extmath.
weighted_mode
(a, w, axis=0)[source]¶ Returns an array of the weighted modal (most common) value in a
If there is more than one such value, only the first is returned. The bincount for the modal bins is also returned.
This is an extension of the algorithm in scipy.stats.mode.
 Parameters
 aarray_like
ndimensional array of which to find mode(s).
 warray_like
ndimensional array of weights for each value
 axisint, optional
Axis along which to operate. Default is 0, i.e. the first axis.
 Returns
 valsndarray
Array of modal values.
 scorendarray
Array of weighted counts for each mode.
See also
Examples
>>> from sklearn.utils.extmath import weighted_mode >>> x = [4, 1, 4, 2, 4, 2] >>> weights = [1, 1, 1, 1, 1, 1] >>> weighted_mode(x, weights) (array([4.]), array([3.]))
The value 4 appears three times: with uniform weights, the result is simply the mode of the distribution.
>>> weights = [1, 3, 0.5, 1.5, 1, 2] # deweight the 4's >>> weighted_mode(x, weights) (array([2.]), array([3.5]))
The value 2 has the highest score: it appears twice with weights of 1.5 and 2: the sum of these is 3.5.