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Answer:
The recursion function is as follows:
def raise_to_power(num, power):
if power == 0:
return 1
elif power == 1:
return num
else:
return (num*raise_to_power(num, power-1))
Explanation:
This defines the function
def raise_to_power(num, power):
If power is 0, this returns 1
if power == 0:
return 1
If power is 1, this returns num
elif power == 1:
return num
If otherwise, it calculates the power recursively
else:
return (num*raise_to_power(num, power-1))
Answer:
Explanation:
The minimum depth occurs for the path that always takes the smaller portion of the
split, i.e., the nodes that takes α proportion of work from the parent node. The first
node in the path(after the root) gets α proportion of the work(the size of data
processed by this node is αn), the second one get (2)
so on. The recursion bottoms
out when the size of data becomes 1. Assume the recursion ends at level h, we have
(ℎ) = 1
h = log 1/ = lg(1/)/ lg = − lg / lg
Maximum depth m is similar with minimum depth
(1 − )() = 1
m = log1− 1/ = lg(1/)/ lg(1 − ) = − lg / lg(1 − )
