get_performance: Extract model performance
In BYUIDSS/BYUImachine: Machine Learning Model Selection of Cognostic Data

Description Usage Arguments Value Author(s) See Also Examples

Generates tibble of performance measures by model, measure and arranged by score

1	get_performance(models, test_x, test_y, format = "long")

`models`	List of models of class `train`
`test_x`	'data.frame' or 'tibble' of explanitory variables
`test_y`	vector of target variable
`format`	"long" for long format (default), or "wide" for wide format

This function returns a tibble of model performance including columns:

model model name
measure machine learning metrics
score double, usually a range between 0 and 1

When format = "wide", the function will return a tibble including columns:

Type
Accuracy - Overall performance of model
Accuracy Lower
Accuracy Null
Accuracy P value
Accuracy Upper
Balanced Accuracy
Detection Prevalence
Detection Rate
F1 - Hybrid metric usefull fr unbalanced classes
Kappa - Compares an observed accuracy with an expected accuracy
McNemar P Value
Negagive Prediction Value
Positive Predictive Value
Precision - How accurate the positive predictions are
Prevalence
Recall - True positive rate, number of instances from the positive class that actually predictoed correctly
Sensitivity - Same as recall
Specificty - Number of instances from the negative class that were actually predicted correctly
Method the algorithm used to train each particular model

"Dallin Webb <dallinwebb@byui.edu>"

extract_measures

## Not run: 
# Long format
p <- get_performance(models_list, test_x, test_y)
p
p %>% filter(measure == "F1")

# Wide format
get_performance(models_list, test_x, test_y, format = "wide")

## End(Not run)