could you give me recursive step please?

- Algorithms and sets In machine learning, clustering can be used to group similar data for prediction and recommendation. For example, each Netflix user's viewing history can be represented as a n-tuple indicating their preferences about movies in the database, where n is the number of movies in the database. Each element in the n-tuple indicate the user's rating of the corresponding movie: 1 indicates the person liked the movie, -1 that they didn't, and 0 that they didn't rate it one way or another. Consider the following algorithm for determining if a user's viewing history represents strong opinions on many movies. Listing 1: Determine if user's ratings tuple encode strong opinions 1 procedure opinion((T1,...,n): a n-tuple of ratings; c: a non negative integer) sum := 0 3 for i:=1 to n 4 if rito sum := sum +1 6 return sum > c - Algorithms and sets In machine learning, clustering can be used to group similar data for prediction and recommendation. For example, each Netflix user's viewing history can be represented as a n-tuple indicating their preferences about movies in the database, where n is the number of movies in the database. Each element in the n-tuple indicate the user's rating of the corresponding movie: 1 indicates the person liked the movie, -1 that they didn't, and 0 that they didn't rate it one way or another. Consider the following algorithm for determining if a user's viewing history represents strong opinions on many movies. Listing 1: Determine if user's ratings tuple encode strong opinions 1 procedure opinion((T1,...,n): a n-tuple of ratings; c: a non negative integer) sum := 0 3 for i:=1 to n 4 if rito sum := sum +1 6 return sum > c