Build transition matrices from text, generate probabilistic sequences
Click Generate to produce text...
Top transitions from last generated word:
Markov chains model sequences where the next state depends only on the current state (the Markov property). An n-gram Markov model uses the last n words to predict the next. The transition matrix T[s][s'] = P(next=s' | current=s) is estimated from corpus frequencies. Higher-order chains produce more coherent text but require exponentially more data. PageRank, speech recognition (HMMs), and DNA sequence analysis all rely on Markov models.