TF-IDF

TF-IDF is a statistical measure used to evaluate the importance of a word in a document relative to a collection of documents, known as a corpus. It combines two metrics: term frequency (TF), which measures how often a term appears in a document, and inverse document frequency (IDF), which assesses how common or rare a term is across the entire corpus. The resulting score helps in identifying the most relevant words for a specific document, making it a key component in information retrieval and text mining. Common use cases include search engines, document classification, and recommendation systems, where understanding the significance of terms is crucial for delivering accurate results.