Mini toolsDefinition
A statistical model where the system is assumed to be a Markov process with hidden states that generate observable outputs.
Detailed Explanation
Hidden Markov Models (HMMs) extend Markov Models by introducing hidden states that are not directly observable but emit observable outputs. The model includes transition probabilities between hidden states and emission probabilities for observations. HMMs use algorithms like Forward-Backward and Viterbi for inference and parameter estimation.
Use Cases
Speech recognition, handwriting recognition, gesture recognition, gene sequence analysis, and natural language processing tasks.
