Package org.nd4j.linalg.api.ops.impl.transforms

Class Summary

Class	Description
Abs	Abs elementwise function
ACos	Log elementwise function
ASin	Arcsin elementwise function
ATan	Arc Tangent elementwise function
Ceil	Ceiling elementwise function
Cos	Cosine elementwise function
ELU	ELU: Exponential Linear Unit (alpha=1.0) Introduced in paper: Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) Djork-Arné Clevert, Thomas Unterthiner, Sepp Hochreiter (2015) http://arxiv.org/abs/1511.07289
ELUDerivative	Derivative of ELU: Exponential Linear Unit (alpha=1.0) Introduced in paper: Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) Djork-Arné Clevert, Thomas Unterthiner, Sepp Hochreiter (2015) http://arxiv.org/abs/1511.07289
Exp	Exp elementwise function
Floor	Floor elementwise function
HardTanh	Hard tanh elementwise function
HardTanhDerivative	Hard tanh elementwise derivative function
Identity	Identity function
LeakyReLU	Leaky Rectified linear unit.
LeakyReLUDerivative	Leaky ReLU derivative.
LinearIndex	Collects the linear indexes for a given vector.
Log	Log elementwise function
LogSoftMax	Log(softmax(X))
MaxOut	Max out activation: http://arxiv.org/pdf/1302.4389.pdf
Negative	Negative function
OneMinus	1 - input
Ones	Ones (represents a constant)
Pow	Pow function
RectifedLinear	Rectified linear units
Round	Rounding function
SetRange	Set range to a particular set of values
Sigmoid	Sigmoid function
SigmoidDerivative	Sigmoid derivative
Sign	Signum function
Sin	Log elementwise function
SoftMax	Soft max function row_maxes is a row vector (max for each row) row_maxes = rowmaxes(input) diff = exp(input - max) / diff.rowSums() Outputs a probability distribution.
SoftMaxDerivative	Softmax derivative
SoftPlus
SoftSign	Softsign element-wise activation function.
SoftSignDerivative	SoftSign derivative.
Sqrt	Sqrt function
Stabilize	Stabilization function, forces values to be within a range
Step	Unit step function.
Tanh	Tanh elementwise function
TanhDerivative	Tanh derivative
TimesOneMinus	If x is input: output is x*(1-x)
VectorFFT	Encapsulated vector operation
VectorIFFT	Single ifft operation