Function reference • cito

All functions

ALE(): Accumulated Local Effect Plot (ALE)

PDP(): Partial Dependence Plot (PDP)

analyze_training(): Visualize training of Neural Network

avgPool(): Average pooling layer

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

cnn(): CNN

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

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(): Convolutional layer

create_architecture(): CNN architecture

dnn(): DNN

e(): Embeddings

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

linear(): Linear layer

maxPool(): Maximum pooling layer

plot(<citoarchitecture>): Plot the CNN architecture

plot(<citocnn>): Plot the CNN architecture

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

predict(<citocnn>): Predict from a fitted cnn model

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

print(<citoarchitecture>): Print class citoarchitecture

print(<citocnn>): Print class citocnn

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

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>): Summary citocnn

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

transfer(): Transfer learning

tune(): Tune hyperparameter