What is longest monotonically increasing subsequence?
A logest monotonically increasing subsequence (LMIS) of A is an increasing subsequence of A of maximum length. Examples. Let A be the sequence 20,50,30,10,40. Then 50,10,40 is a subsequence of A even though it is not monotonically increasing.
Which of the following methods can be used to solve the longest common subsequence problem?
Which of the following methods can be used to solve the longest common subsequence problem? Explanation: Both recursion and dynamic programming can be used to solve the longest subsequence problem.
What is the time complexity of longest increasing subsequence?
Longest Increasing Subsequence
 Example 1: Input: A = [10,9,2,5,3,7,101,18] Output: 4 Explanation: The longest increasing subsequence is [2,3,7,101], therefore the length is 4.
 Example 2:
 Example 3:
 Space Complexity: O(1) , no additional space reserved.
 Space Complexity: O(n) , for storing the memoized solutions.
How do you find the longest increasing subsequence in Python?
Longest Increasing Subsequence in Python
 trail := an array of length 0 to length of nums – 1, and fill this with 0.
 size := 0.
 for x in nums. i := 0, j := size. while i is not j. mid := i + (j – i) / 2. if trails[mid] < x, then i := mid + 1, otherwise j := mid. trails[i] := x. size := maximum of i + 1 and size.
 return size.
What are the applications of the longest common subsequence?
The longest common subsequence problem is a classic computer science problem, the basis of data comparison programs such as the diff utility, and has applications in computational linguistics and bioinformatics.
What is longest common subsequence explain with example?
Let us understand LCS with an example. Then, common subsequences are {B, C}, {C, D, A, C}, {D, A, C}, {A, A, C}, {A, C}, {C, D}, Among these subsequences, {C, D, A, C} is the longest common subsequence. We are going to find this longest common subsequence using dynamic programming.
What is the application of the longest common subsequence?
Which of the following method can be used to solve the longest?
D. Explanation: both recursion and dynamic programming can be used to solve the longest subsequence problem.
How do you find the subsequence of a list in Python?
“find all subsequences of a list python” Code Answer
 # from https://www.askpython.com/python/examples/possiblesubsequencessubsets.

 def get_all_subsequence(n, output, i):
 if (i == len(n)):
 if (len(output) != 0):
 print(output)
 else:
 # exclude first character.
What is monotonically increasing sequences?
Monotonically increasing just means the numbers in the subsequence don’t decrease, they can stay even. Otherwise, example 6 would only have one 6 in the front. Let’s start by creating a function called lis (for “longest increasing subsequence”). It will take one parameter, a list.
What is the length of the longest increasing subsequence?
An increasing subsequence is a subsequence with its elements in increasing order. You need to find the length of the longest increasing subsequence that can be derived from the given array. Explanation: The longest increasing subsequence is {3,10,20}.
What are the longest increasing subscriptions with same length?
As we can see from the list, the longest increasing subsequence is {3, 5, 12, 15} with length 4. However, it’s not the only solution, as {3, 10, 12, 15} is also the longest increasing subsequence with equal length.
Why do we need to maintain lists of increasing sequences?
To make it clear, consider the array is {2, 5, 3, 1, 2, 3, 4, 5, 6}. Making 1 as new sequence will create new sequence which is largest. The observation is, when we encounter new smallest element in the array, it can be a potential candidate to start new sequence. From the observations, we need to maintain lists of increasing sequences.