RankNet

RankNet is a machine learning algorithm designed to order or rank items based on their relevance or importance. It learns by comparing pairs of items to determine which should come higher in the ranking. During training, it evaluates pairs, adjusting its internal parameters to improve its ability to predict which item is better suited for a particular position. This approach is useful in applications like search engines, where it's important to present the most relevant results first. Essentially, RankNet learns to make more accurate rankings by focusing on pairwise comparisons rather than scoring items individually.