Projecting a vector to another to detect the sparse values of such vector

1. How do you represent a sparse vector?
2. How to store sparse vectors?
3. What is meant by sparse vector in information retrieval?
4. What is sparse vector in Python?

How do you represent a sparse vector?

One possibility is to represent the elements of a sparse vector as a linked list of nodes, each of which contains an integer index, a numerical value, and a pointer to the next node.

How to store sparse vectors?

To store the Sparse Vector efficiently we only store the non-zero values of the vector along with the index. The First element of pair will be the index of sparse vector element(which is non-zero) and the second element will be the actual element. We are using TreeMap as the vector for the index-value pairs.

What is meant by sparse vector in information retrieval?

A sparse vector is a vector having a relatively small number of nonzero elements. Consider the following as an example of a sparse vector x with n elements, where n is 11, and vector x is: (0.0, 0.0, 1.0, 0.0, 2.0, 3.0, 0.0, 4.0, 0.0, 5.0, 0.0) In Storage.

What is sparse vector in Python?

A sparse vector is a vector whose entries are almost all zero, like [1, 0, 0, 0, 0, 0, 0, 2, 0] . Storing all those zeros wastes memory and dictionaries are commonly used to keep track of just the nonzero entries.