The hard sigmoid function, defined by.
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#include <hard_sigmoid_function.hpp>
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static double | Fn (const double x) |
| Computes the hard sigmoid function. More...
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template<typename InputVecType , typename OutputVecType > |
static void | Fn (const InputVecType &x, OutputVecType &y) |
| Computes the hard sigmoid function. More...
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static double | Deriv (const double y) |
| Computes the first derivatives of hard sigmoid function. More...
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template<typename InputVecType , typename OutputVecType > |
static void | Deriv (const InputVecType &y, OutputVecType &x) |
| Computes the first derivatives of the hard sigmoid function. More...
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The hard sigmoid function, defined by.
\begin{eqnarray*} f(x) &=& \min(1, \max(0, 0.2 * x + 0.5)) \\ f'(x) &=& \left\{ \begin{array}{lr} 0.0 & : x={0,1} \\ 0.2 \end{array} \right. \end{eqnarray*}
◆ Deriv() [1/2]
static double mlpack::ann::HardSigmoidFunction::Deriv |
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const double |
y | ) |
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inlinestatic |
Computes the first derivatives of hard sigmoid function.
- Parameters
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- Returns
- f'(x)
◆ Deriv() [2/2]
template<typename InputVecType , typename OutputVecType >
static void mlpack::ann::HardSigmoidFunction::Deriv |
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const InputVecType & |
y, |
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OutputVecType & |
x |
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) |
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inlinestatic |
Computes the first derivatives of the hard sigmoid function.
- Parameters
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y | Input data. |
x | The resulting derivatives. |
◆ Fn() [1/2]
static double mlpack::ann::HardSigmoidFunction::Fn |
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const double |
x | ) |
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inlinestatic |
Computes the hard sigmoid function.
- Parameters
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- Returns
- f(x).
◆ Fn() [2/2]
template<typename InputVecType , typename OutputVecType >
static void mlpack::ann::HardSigmoidFunction::Fn |
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const InputVecType & |
x, |
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OutputVecType & |
y |
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) |
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inlinestatic |
Computes the hard sigmoid function.
- Parameters
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x | Input data. |
y | The resulting output activations. |
The documentation for this class was generated from the following file: