logistic.acc

0th

Percentile

Contingency table: Predicted vs. Observed Outcomes

This function takes predicted probabilities (for out of bag cases) obtained through logistic regression-based tree models and converts them into binary classes (based on specified probability threshold). The predicted classifications are then compared to actual binary response.

Usage
logistic.acc(response, predicted, prob_thresh = 0.5)
Arguments
response

A vector of binary classes of out-of-cases for a given tree.

predicted

A vector of predicted probabilities of out-of-cases using same tree.

prob_thresh

Probability threshold for classification (default = .5).

Aliases
  • logistic.acc
Examples
# NOT RUN {
# We should get 15 predictions correct and miss 5
response <- matrix(c(rep(0,10), rep(1,10)))
predicted <- c(rep(.1,15), rep(.8,5))
logistic.acc(response, predicted, .5)	

# }
Documentation reproduced from package mobForest, version 1.3.1, License: GPL (>= 2)

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