Mine Contexts by Next-State Probability

Scan every context in a fitted tree for a chosen next state and return those whose predicted probability for that state falls in a requested range. A tidy context-mining table: "in which histories is the next move state unusually likely or unlikely?"

Usage

mine_contexts(tree, state, min_prob = NULL, max_prob = NULL, min_count = 1L)

Arguments

tree

A transitiontrees.

state

Character. The next state to score, one of the tree's alphabet.

min_prob, max_prob

Numeric in \([0, 1]\) or NULL. Keep contexts whose P(state | context) is at least min_prob and/or at most max_prob. NULL (default) leaves that side unbounded.

min_count

Integer. Drop contexts with fewer than this many occurrences. Default 1.

Value

A data.frame with columns pathway, depth, count, state, prob (P(state | context)), and is_modal (whether state is the context's most likely next state; ties broken by alphabet order), sorted by prob descending. The empty case returns a 0-row data.frame with the same schema.

Examples

seqs <- replicate(60, sample(c("A", "B", "C"), 10, replace = TRUE),
                  simplify = FALSE)
tree <- context_tree(seqs, max_depth = 2L)
mine_contexts(tree, state = "A", min_prob = 0.4)
#>   pathway depth count state      prob is_modal
#> 1  A -> B     2    54     A 0.4259259     TRUE
#> 2  C -> A     2    45     A 0.4000000     TRUE