kerasCreateModelCNN_2d: Function used to create a 2d CNN model

In kristianHoden/smartPARE: An R package for efficient identification of true mRNA cleavage sites

Description

The model is used to train a Convolutional neural network model that can recognize images

Usage

kerasCreateModelCNN_2d(
  denseLoop = 3,
  testPics,
  trainLabels,
  epochs,
  batch_size,
  dropout = 0.2,
  patience = 0,
  validation_split,
  activation = "relu",
  activationFinal = "softmax",
  pixels = 28,
  optimizer = "adam",
  convolutionalLoop = 2,
  NO_pooling = 1
)

Arguments

denseLoop	Number of times to iterate the dense layers loops
testPics	Image info object generated by kerasCreateDataset_2d
trainLabels	trainLabels object generated by
epochs	Number of epochs in keras
batch_size	Batch size in keras
dropout	Keras dropout
patience	EarlyStopping patience
validation_split	Fraction of the dataset that will be used for validation
activation	Standard function activation
activationFinal	Final activation function of the model
pixels	Pixel size of the images, assigned in kerasCreateDataset_2d
optimizer	Optimizer
convolutionalLoop	Number of times to iterate the convolutional layers loop
NO_pooling	Number of times to perform pooling in the convolutional layers loop (max = 2)

Examples

kerasCreateModelCNN_2d(testPics,
trainLabels,
denseLoop = 3,
epochs,
batch_size,
dropout = 0.2,
patience = 0,
validation_split,
activation = "relu",
activationFinal = "softmax",
pixels =28,
optimizer = "adam",
convolutionalLoop = 2,
NO_pooling = 1
)

kristianHoden/smartPARE documentation built on July 3, 2021, 7:10 p.m.