.ipynb_checkpoints/create.mlp-checkpoint: Initializes a new neural network.
In Greg-Hallenbeck/easy.mlp: Easy-To-Use Multilayer Perceptron
create.mlp R Documentation
Initializes a new neural network.
Description
Initializes a new neural network.
Usage
create.mlp(
formula,
data = NULL,
hidden = c(),
type = NULL,
activation = "leaky.relu",
valid.split = 0.25,
randomize = TRUE,
learning.rate = 0.001,
momentum.beta = 0.9,
rmsprop.beta = 0.999,
batch.size = 64
)
Arguments
formula
An object of class 'formula' describing the model to be fit.
data
A 'data.frame' object containing the training and validation data.
hidden
A vector indicating how many layers and hidden notes the network will have. Passing c(4,5,2) creates a network with 3 hidden layers with 4, 5, and 2 nodes, respectively.
type
One of "regression", "logistic", or "classification".
activation
The name of a function to be used for activations in the hidden layers. "leaky.relu", "relu", "tanh", and "sigmoid" are included in the package.
learning.rate
The learning rate of the network.
momentum.beta
Beta parameter for gradient descent with momentum.
batch.size
Minibatch size. Choosing 1 is equivalent to stochastic gradient descent.
rmpsprop.beta
Beta parameter for RMSprop gradient descent.
Examples
create.mlp(Species ~ ., data=iris, hidden=c(5,5,5), type="classification")
Greg-Hallenbeck/easy.mlp documentation built on March 10, 2023, 6:31 a.m.
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| create.mlp | R Documentation |
Initializes a new neural network.
Description
Initializes a new neural network.
Usage
create.mlp( formula, data = NULL, hidden = c(), type = NULL, activation = "leaky.relu", valid.split = 0.25, randomize = TRUE, learning.rate = 0.001, momentum.beta = 0.9, rmsprop.beta = 0.999, batch.size = 64 )
Arguments
formula |
An object of class 'formula' describing the model to be fit. |
data |
A 'data.frame' object containing the training and validation data. |
hidden |
A vector indicating how many layers and hidden notes the network will have. Passing c(4,5,2) creates a network with 3 hidden layers with 4, 5, and 2 nodes, respectively. |
type |
One of "regression", "logistic", or "classification". |
activation |
The name of a function to be used for activations in the hidden layers. "leaky.relu", "relu", "tanh", and "sigmoid" are included in the package. |
learning.rate |
The learning rate of the network. |
momentum.beta |
Beta parameter for gradient descent with momentum. |
batch.size |
Minibatch size. Choosing 1 is equivalent to stochastic gradient descent. |
rmpsprop.beta |
Beta parameter for RMSprop gradient descent. |
Examples
create.mlp(Species ~ ., data=iris, hidden=c(5,5,5), type="classification")
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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