## TestingAnalysis class

This is the documentation for the python TestingAnalysis class methods in the OpenNN python module.

This class contains tools for testing neural networks in different learning tasks. In particular, it can be used for testing function regression, classification or time series prediction problems.

#### Initialization methods

TestingAnalysis()

TestingAnalysis(new_neural_networ,new_data_set)

- new_neural_networ Pointer to a neural network object.
- new_data_set Pointer to a data set object.
`TestingAnalysis(file_name)`

- file_name Name of testing analysis XML file.

Default initialization method. It creates a testing analysis object neither associated to a neural network nor to a mathematical model or a data set. By default, it constructs the function regression testing object.

Neural network and data set initialization method. It creates a testing analysis object associated to a neural network and to a data set. By default, it constructs the function regression testing object.

File initialization method. It creates a testing analysis object neither associated to a neural network nor to a mathematical model or a data set. It also loads the members of this object from XML file.

#### General methods

perform_linear_regression_analysis()

linear_regression_correlations()

Perform a linear regression between predicted and actual values for target variables.

Get the linear regression correlation for the target variables.