Rank Information

Learning to rank or machine-learned ranking (MLR) is the application of machine learning, typically supervised, semi-supervised or reinforcement learning, in the construction of ranking models for information retrieval systems. Training data consists of lists of items with some partial order specified between items in each list. The Times Higher Education World University Rankings 2021 include more than 1,500 universities across 93 countries and regions, making them the largest and most diverse university rankings to date. The table is based on 13 carefully calibrated performance indicators that measure an institution’s performance across four areas: teaching. Learning to rank refers to machine learning techniques for training the model in a ranking task. Learning to rank is useful for many applications in information retrieval, natural language processing, and data mining. Intensive studies have been conducted on the problem recently.
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Rank Information Coefficient
- Kentucky ranks 13th among U.S. States for affordability. It ranks 3rd for equality and 11th for crime & corrections.
- Windows saves this information in a driver store database for internal use. When Windows installs a driver, SetupAPI adds a Rank entry that logs the driver rank in hexadecimal format and a Signer Score entry that logs the signature type.
