NGram Model
An n-gram model is a probabilistic language model that predicts or represents text based on sequences of n consecutive words (or characters), estimating the probability of a word given the preceding n-1 words using frequency counts from a training corpus.
5 resources across 1 library
Glossary Terms(5)
GloVe Embeddings
GloVe (Global Vectors for Word Representation) is an unsupervised word embedding algorithm developed at Stanford that learns dense vector representations of wo…
TF-IDF
TF-IDF (Term Frequency-Inverse Document Frequency) is a numerical statistic used to measure how important a word is to a specific document within a larger coll…
Bag of Words
Bag of Words is a simple text representation technique that converts a document into a vector of word counts or frequencies, disregarding grammar, word order,…
N-gram Model
An n-gram model is a probabilistic language model that predicts or represents text based on sequences of n consecutive words (or characters), estimating the pr…
Greedy Decoding
Greedy decoding is a text generation strategy in which a language model selects the single highest-probability token at each generation step, without consideri…