Matching is one of the basic machine learning tasks found in information retrieval, computer vision, recommender systems, etc.
🔸 Develop an algorithm that for all items from given validation dataset will suggest several options of the most similar products from base;
🔸 Evaluate the performance using Accuracy@5 metric.
Overall, a search for the nearest 5 items on base for items from the validation dataset using Annoy Index showed an accuracy@5 metric of
To check the results, you may see val_5_targets.csv in the results directory. This dataset contains the following features: id for the validation query (id), 5 nearest neighbours obtained for each query (target_0-target_4), and the expected most similar result for a query (expected) derived from the given validation_answers.