No it is not equal. 3.55 divided by 5=0.71. 0.3 divided by 5+ 0.05 divided by 5 equals to 0.07.
When you have the same denominator. Other than that have different denominators will not be possible.
The purpose of the tensor-on-tensor regression, which we examine, is to relate tensor responses to tensor covariates with a low Tucker rank parameter tensor/matrix without being aware of its intrinsic rank beforehand.
By examining the impact of rank over-parameterization, we suggest the Riemannian Gradient Descent (RGD) and Riemannian Gauss-Newton (RGN) methods to address the problem of unknown rank. By demonstrating that RGD and RGN, respectively, converge linearly and quadratically to a statistically optimal estimate in both rank correctly-parameterized and over-parameterized scenarios, we offer the first convergence guarantee for the generic tensor-on-tensor regression. According to our theory, Riemannian optimization techniques automatically adjust to over-parameterization without requiring implementation changes.
Learn more about tensor-on-tensor here
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Answer:
probability = 0.2517
Step-by-step explanation:
given data
boy kittens = 9
girl kittens = 6
choose kittens at random = 9
solution
total kitten are = 9 + 6 = 15
first we get here total no of probability that is
n(s) = 15 C 9
n(s) = 
n(s) =5005
and
total way to chose 5 boy kittens is = 9 C 3
n(3) = 
n(3) = 84
and
total way to chose 4 girl kittens is = 6 C 4
n(4) = 
n(4) = 15
so
total way to chose 5 boy kittens and 4 girl kittens is
total way = 84 ×15 = 1260
so probability that the director chooses 5 boy kittens and 4 girl kittens is
probability = 
probability = 0.2517
