accuracy: Confusion matrix and overall accuracy of predicted binary...
In StatMeasures: Easy Data Manipulation, Data Quality and Statistical Checks

Description Usage Arguments Details Value Author(s) See Also Examples

Takes in actual binary response, predicted probabilities and cutoff value, and returns confusion matrix and overall accuracy

1	accuracy(y, yhat, cutoff)

`y`	actual binary response variable
`yhat`	predicted probabilities corresponding to the actual binary response
`cutoff`	threshold value in the range 0 to 1

When we predict a binary response, first thing that we want to check is accuracy of the model for a particular cutoff value. This function does just that and provides confusion matrix (numbers and percentage) and overall accuracy. Overall accuracy is calculated as (TP + TN)/(P + N).

The output is a list from which the individual elements can be picked as shown in the example.

a three element list: confusion matrix as a table, confusion matrix (percentages) as a table and overall accuracy value

Akash Jain

ks, auc, iv, splitdata

# A 'data.frame' with y and yhat
df <- data.frame(y = c(1, 0, 1, 1, 0),
                 yhat = c(0.86, 0.23, 0.65, 0.92, 0.37))

# Accuracy tables and overall accuracy figures
ltAccuracy <- accuracy(y = df[, 'y'], yhat = df[, 'yhat'], cutoff = 0.7)
accuracyNumber <- ltAccuracy$accuracyNum
accuracyPercentage <- ltAccuracy$accuracyPer
overallAccuracy <- ltAccuracy$overallAcc