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Optimal binary search tree
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Given a sorted array keys[0.. n-1] of search keys and an array freq[0.. n-1] of frequency counts, where freq[i] is the number of searches to keys[i]. Construct a binary search tree of all keys such that the total cost of all the searches is as small as possible.
Let us first define the cost of a BST. The cost of a BST node is level of that node multiplied by its frequency. Level of root is 1.


Example 1:

Input:
n = 2
keys = {10, 12}
freq = {34, 50}
Output: 118
Explaination:
There can be following two possible BSTs 
        10                       12
          \                     / 
           12                 10
          <I>                    <II>
The cost of tree I is 34*1 + 50*2 = 134
The cost of tree II is 50*1 + 34*2 = 118 


Example 2:

Input:
N = 3
keys = {10, 12, 20}
freq = {34, 8, 50}
Output: 142
Explaination: There can be many possible BSTs
     20
    /
   10  
    \
     12  
     <I>
Among all possible BSTs, cost of this BST is minimum.  
Cost of this BST is 1*50 + 2*34 + 3*8 = 142


Your Task:
You don't need to read input or print anything. Your task is to complete the function optimalSearchTree() which takes the array keys[], freq[] and their size as input parameters and returns the total cost of all the searches is as small as possible.


Expected Time Complexity: O(n3)
Expected Auxiliary Space: O(n2)


Constraints:
1 ≤ N ≤ 100

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Optimal binary search tree

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