AUTO_VI |
AUTO_VI class environment |
auto_vi |
AUTO_VI class environment |
AUTO_VI$..init.. |
Initialization method |
AUTO_VI$..str.. |
String representation of the object |
AUTO_VI$auxiliary |
Compute auxiliary variables for the keras model |
AUTO_VI$boot_vss |
Predict visual signal strength for bootstrapped residual plots |
AUTO_VI$check |
Conduct a auto visual inference check with a computer vision model |
AUTO_VI$check_result |
List of diagnostic results |
AUTO_VI$feature_pca |
Conduct principal component analysis for features extracted from keras model |
AUTO_VI$feature_pca_plot |
Draw a summary Plot for principal component analysis conducted on extracted features |
AUTO_VI$get_data |
Get data out of a model object |
AUTO_VI$get_fitted_and_resid |
Get fitted values and residuals out of a model object |
AUTO_VI$likelihood_ratio |
Compute the likelihood ratio using the simulated result |
AUTO_VI$lineup_check |
Conduct a auto visual inference lineup check with a computer vision model |
AUTO_VI$null_method |
Get null residuals from a fitted model |
AUTO_VI$null_vss |
Simulate null plots and predict the visual signal strength |
AUTO_VI$plot_resid |
Draw a standard residual plot |
AUTO_VI$p_value |
Compute the p-value based on the check result |
AUTO_VI$rotate_resid |
Get rotated residuals from a fitted linear model |
AUTO_VI$select_feature |
Select features from the check result |
AUTO_VI$summary_density_plot |
Draw a summary density plot for the result |
AUTO_VI$summary_plot |
Draw a summary plot for the result |
AUTO_VI$summary_rank_plot |
Draw a summary rank plot for the result |
AUTO_VI$vss |
Predict the visual signal strength |
check_python_library_available |
Check python library availability |
get_keras_model |
Download and load the keras model |
KERAS_WRAPPER |
KERAS_WRAPPER class environment |
keras_wrapper |
KERAS_WRAPPER class environment |
KERAS_WRAPPER$..init.. |
Initialization method |
KERAS_WRAPPER$..str.. |
String representation of the object |
KERAS_WRAPPER$get_input_height |
Get keras model input image height |
KERAS_WRAPPER$get_input_width |
Get keras model input image width |
KERAS_WRAPPER$image_to_array |
Load an image as numpy array |
KERAS_WRAPPER$list_layer_name |
List all layer names |
KERAS_WRAPPER$predict |
Predict visual signal strength |
list_keras_model |
List all available pre-trained computer vision models |
remove_plot |
Remove a plot |
save_plot |
Save a plot |