Returns the list of windows that come after param win (str)

Returns series of conditional probs for succeeding window(s) for a given win

Returns transisiton matrix for the HMM and creates the n x n transistion matrix with n = num of unique windows indices is the order of window_order rows denote prob for window_order[win] for every other window

Returns the conditional immersive window probabilities

Returns emission matrix using only emmersive probabilty

Cleans csv and outputs either a windows df OR windows and is_immersive df

Splits data into train and test portions, default 80-20 split Training data is first train_size % of the data Test data is last test_size % of the data

This predictor outputs the top x probable windows and checks the current test data window if it's in the top x. if not then a check mark of incorrect is added. Accuracy is outputted at the end

This predictor ouputs a sequence of next windows. Accuracy is measured AFTER

This predictor outputs the top x probable windows and checks the current test data window if it's in the top x AND fits is_immersive emission matrix value if not then a check mark of incorrect is added accuracy is outputted at the end