DataReporting¶
Submodules¶
reporting module¶
-
hardy.data_reporting.reporting.model_analysis(model, test_set, test_set_list=None)[source]¶ The function that provides analysis of a trained model for its predicted output and actual output
Parameters: - model: keras.model
a keras instance of the trained model to use for the prediction
- test_set_list: list
list representing the file names, images and labels for test set.
- test_set: keras.ImageDataGenerator iterator
the interator instance created using the keras.ImageDataGenerator. This can either be a NumpyArrayIterator or a DirectoryIterator
Returns: - result: pandas.DataFrame
dataframe having filenames, actual labels, predicted labels and probability for decision
-
hardy.data_reporting.reporting.model_predictions(model, test_set, classes, test_set_list=None)[source]¶ The function that provides predictions using a trained model
Parameters: - model: keras.model
a keras instance of the trained model to use for the prediction
- test_set_list: list
list representing the file names, images and labels for test set.
- classes: list
list representing classes. Must be in same order as used for training the model
- test_set: keras.ImageDataGenerator iterator
the interator instance created using the keras.ImageDataGenerator. This can either be a NumpyArrayIterator or a DirectoryIterator
Returns: - result: pandas.DataFrame
dataframe having filenames, actual labels, predicted labels and probability for decision
-
hardy.data_reporting.reporting.summary_report_plots(report_path)[source]¶ The function that plots the parallel coordinates between report name, layers, optimizer, activation function, kernel size, pooling and accuracy.
Parameters: - report_path: str
string representing the location of parent report directory
-
hardy.data_reporting.reporting.summary_report_tables(report_path)[source]¶ The function that returns tables wiht the summary of the transformations used and they performnce
Parameters: - report_path: str
string representing the location of parent report directory
Returns: - summary_df : pandas Dataframe
Table containing information of the transformations run, which data series they were applied to and their plot format
- tform_rank_df : pandas Dataframe
Table containing information of the run anme and its overall performance