Package index • cito

All functions

ALE(): Accumulated Local Effect Plot (ALE)

PDP(): Partial Dependence Plot (PDP)

analyze_training(): Visualize training of Neural Network

avgPool(): This function creates an avgPool layer object of class citolayer for use in constructing a Convolutional Neural Network (CNN) architecture. The resulting layer object can be passed to the create_architecture function to define the structure of the network.

cito cito-package: 'cito': Building and training neural networks

cnn(): Train a Convolutional Neural Network (CNN)

coef(<citocnn>): Retrieve parameters of a fitted CNN model

coef(<citodnn>) coef(<citodnnBootstrap>): Returns list of parameters the neural network model currently has in use

conditionalEffects(): Calculate average conditional effects

config_lr_scheduler(): Creation of customized learning rate scheduler objects

config_optimizer(): Creation of customized optimizer objects

config_tuning(): Config hyperparameter tuning

continue_training(): Continues training of a model generated with dnn or cnn for additional epochs.

conv(): Create a Convolutional Layer for a CNN Architecture

create_architecture(): Create a CNN Architecture

dnn(): DNN

e(): Embeddings

findReTrmClasses(): list of specials – taken from enum.R

linear(): Create a Linear Layer for a CNN Architecture

maxPool(): Create a Maximum Pooling Layer for a CNN Architecture

mmn(): Train and evaluate a Multi-Modal Neural Network (MMN) model

multinomial_log_prob(): Multinomial log likelihood

plot(<citoarchitecture>): Plot method for citoarchitecture objects

plot(<citocnn>): Plot a fitted CNN model

plot(<citodnn>) plot(<citodnnBootstrap>): Creates graph plot which gives an overview of the network architecture.

predict(<citocnn>): Predict with a fitted CNN model

predict(<citodnn>) predict(<citodnnBootstrap>): Predict from a fitted dnn model

predict(<citommn>): Predict from a fitted mmn model

print(<citoarchitecture>): Print method for citoarchitecture objects

print(<citocnn>): Print a fitted CNN model

print(<citodnn>) print(<citodnnBootstrap>): Print class citodnn

print(<citommn>): Print class citommn

print(<conditionalEffects>) print(<conditionalEffectsBootstrap>): Print average conditional effects

print(<summary.citodnn>) print(<summary.citodnnBootstrap>): Print method for class summary.citodnn

residuals(<citodnn>): Extract Model Residuals

simulate_shapes(): Data Simulation for CNN

sumTerms(): combine a list of formula terms as a sum

summary(<citocnn>): Summarize a fitted CNN model

summary(<citodnn>) summary(<citodnnBootstrap>): Summarize Neural Network of class citodnn

summary(<citommn>): Summary citommn

transfer(): Include a Pretrained Model in a CNN Architecture

tune(): Tune hyperparameter