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Create a classification_result instance

classification_result.Rd

Constructs a classification result object based on the observed and predicted values, as well as other optional parameters.

Usage

classification_result(
  observed,
  predicted,
  probs,
  testind = NULL,
  test_design = NULL,
  predictor = NULL
)

Arguments

observed

A vector of observed or true values.

predicted

A vector of predicted values.

probs

A matrix of predicted probabilities, with one column per level.

testind

The row indices of the test observations (optional).

test_design

An optional design for the test data.

predictor

An optional predictor object.

Value

A classification result object, which can be one of: regression_result,

binary_classification_result, or multiway_classification_result.

See also

Other classification_result: binary_classification_result(), multiway_classification_result(), regression_result()

Examples

# A vector of observed values
yobs <- factor(rep(letters[1:4], 5))

# Predicted probabilities
probs <- data.frame(a = runif(1:20), b = runif(1:20), c = runif(1:20), d = runif(1:20))
probs <- sweep(probs, 1, rowSums(probs), "/")

# Get the max probability per row and use this to determine the predicted class
maxcol <- max.col(probs)
predicted <- levels(yobs)[maxcol]

# Construct a classification result
cres <- classification_result(yobs, predicted, probs)

# Compute default performance measures (Accuracy, AUC)
performance(cres)
#>    Accuracy         AUC 
#>  0.20000000 -0.02666667