API Reference - Models - Markov
Constructors
new()
Creates a new base model object. If any of the arguments are nil, default argument values for that argument will be used.
Markov.new(learningRate: number, isHidden: boolean, StatesList: {any}, ObservationsList: {any}): ModelObject
Parameters:
-
learningRate: The speed at which the algorithm learns. Recommended to set between 0 and 1.
-
isHidden: Set whether or not this Markov Model is a Hidden Markov Model.
-
StatesList: A list containing all the states.
-
ObservationsList: A list containing all the observations.
Returns:
- ModelObject: The generated model object.
Functions
train()
Markov:train(previousStateVector, currentStateVector, observationStateVector)
Parameters:
-
previousStateMatrix: A matrix containing all previous state data.
-
currentStateMatrix: A matrix containing all current state data.
predict()
Predict the values for given data.
Markov:predict(previousStateMatrix: matrix, returnOriginalOutput: boolean): matrix, matrix -OR- matrix
Parameters:
-
previousStateMatrix: A matrix containing all previous state data.
-
returnOriginalOutput: Set whether or not to return predicted current state matrix instead of value with highest probability.
Returns:
-
predictedVector: A vector that is predicted by the model.
-
probabilityVector: A vector that contains the probability of predicted values in predictedVector.
-OR-
- predictedCurrentStateMatrix: A matrix containing all predicted values from all classes.