tf.keras.ops.quantile
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Compute the q-th quantile(s) of the data along the specified axis.
tf.keras.ops.quantile(
x, q, axis=None, method='linear', keepdims=False
)
Args |
x
|
Input tensor.
|
q
|
Probability or sequence of probabilities for the quantiles to
compute. Values must be between 0 and 1 inclusive.
|
axis
|
Axis or axes along which the quantiles are computed. Defaults to
axis=None which is to compute the quantile(s) along a flattened
version of the array.
|
method
|
A string specifies the method to use for estimating the
quantile. Available methods are "linear" , "lower" , "higher" ,
"midpoint" , and "nearest" . Defaults to "linear" .
If the desired quantile lies between two data points i < j :
"linear" : i + (j - i) * fraction , where fraction is the
fractional part of the index surrounded by i and j .
"lower" : i .
"higher" : j .
"midpoint" : (i + j) / 2
"nearest" : i or j , whichever is nearest.
|
keepdims
|
If this is set to True , the axes which are reduce
are left in the result as dimensions with size one.
|
Returns |
The quantile(s). If q is a single probability and axis=None , then
the result is a scalar. If multiple probabilies levels are given, first
axis of the result corresponds to the quantiles. The other axes are the
axes that remain after the reduction of x .
|
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Last updated 2024-06-07 UTC.
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