classificationStats: calculate prediction performance statistics for binary...

In HannaMeyer/sptm: Supporting functions for spatio-temporal models using machine learning

Description

this function calculates prediction performance statistics between vectors of predicted and observed values.

Usage

classificationStats(prd, obs, prob = NULL)

Arguments

prd	factor vector of predicted values with two levels
obs	factor vector of observed values with two levels
prob	optional. Predicted probabilities for the first class

Value

data frame containing the classification statistics.

Author(s)

Hanna Meyer

See Also

regressionStats

Examples

#create two random vectors with classes "yes" and "no" to simulate a model
#with random performance. Expected POD and PFD =50%
pred_vals <- factor(sample(c("Yes","No"), 50, replace = TRUE),levels=c("Yes","No"))
obs_vals <- factor(sample(c("Yes","No"), 50, replace = TRUE),levels=c("Yes","No"))

result <- classificationStats(pred_vals, obs_vals)
result

HannaMeyer/sptm documentation built on May 15, 2019, 4:29 p.m.