For a change in this sub- An actual Data Science question

I have created a Content Based Recommender using k-NN to recommend the 5 most similar books within a corpus. The corpus has been processed using nltk and I have applied TF-IDF Vectoriser from sklearn to get in the form of an array.

It works well, but I need to objectively assess it, and I have decided to use Normalised Discounted Cumulative Gain (NDCG).

How do I assess the test data against the training using NDCG? Do I need to create …

array books change data data science datascience form nltk science sklearn tf-idf