mlpy.stats.partitioned_mean¶
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mlpy.stats.
partitioned_mean
(x, y, c=None, return_counts=False)[source]¶ Mean of groups.
Groups the rows of x according to the class labels in y and takes the mean of each group.
Parameters: x : array_like, shape (n, dim)
The data to group, where n is the number of data points and dim is the dimensionality of each data point.
y : array_like, shape (n,)
The class label for each data point.
return_counts : bool
Whether to return the number of elements in each group or not.
Returns: mean : array_like
The mean of each group.
counts : int
The number of elements in each group.
Examples
>>> partitioned_mean()