confidence_95

imagepypelines.confidence_95(data)[source]
returns the 95% confidence mean and deviation for the given
distribution
Parameters:data (array-like) – data to find the confidence interval for, in machine learning applications, this is usually accuracy for K-fold cross validation
Returns:the mean for this distributions float: +/- deviation for this confidence interval
Return type:float

Example

>>> import numpy as np
>>> import imagepypelines as ip
>>> # create sample test 'accuracies' from a normal distribution
>>> # mean accuracy is 75%, std is 10% for this example
>>> accuracies = np.random.normal(.75, .1, 1000)
>>> # get 95% confidence interval
>>> mean, error = ip.confidence_95(accuracies)