fann_train.h

python 神经网络 数据挖掘 python实现的神经网络算法

																enum fann_activationfunc_enum
																activation_function);


/* Function: fann_set_activation_function_output

   Set the activation function for the output layer.

   See also:
   	<fann_set_activation_function>, <fann_set_activation_function_layer>,
   	<fann_set_activation_function_hidden>, <fann_set_activation_steepness_output>

   This function appears in FANN >= 1.0.0.
 */ 
FANN_EXTERNAL void FANN_API fann_set_activation_function_output(struct fann *ann,
																enum fann_activationfunc_enum
																activation_function);

/* Function: fann_get_activation_steepness

   Get the activation steepness for neuron number *neuron* in layer number *layer*, 
   counting the input layer as layer 0. 
   
   It is not possible to get activation steepness for the neurons in the input layer.
   
   The steepness of an activation function says something about how fast the activation function 
   goes from the minimum to the maximum. A high value for the activation function will also
   give a more agressive training.
   
   When training neural networks where the output values should be at the extremes (usually 0 and 1, 
   depending on the activation function), a steep activation function can be used (e.g. 1.0).
   
   The default activation steepness is 0.5.
   
   Returns:
    The activation steepness for the neuron or -1 if the neuron is not defined in the neural network.
   
   See also:
   	<fann_set_activation_steepness_layer>, <fann_set_activation_steepness_hidden>,
   	<fann_set_activation_steepness_output>, <fann_set_activation_function>,
    <fann_set_activation_steepness>

   This function appears in FANN >= 2.1.0
 */ 
FANN_EXTERNAL fann_type FANN_API fann_get_activation_steepness(struct fann *ann,
																int layer,
																int neuron);

/* Function: fann_set_activation_steepness

   Set the activation steepness for neuron number *neuron* in layer number *layer*, 
   counting the input layer as layer 0. 
   
   It is not possible to set activation steepness for the neurons in the input layer.
   
   The steepness of an activation function says something about how fast the activation function 
   goes from the minimum to the maximum. A high value for the activation function will also
   give a more agressive training.
   
   When training neural networks where the output values should be at the extremes (usually 0 and 1, 
   depending on the activation function), a steep activation function can be used (e.g. 1.0).
   
   The default activation steepness is 0.5.
   
   See also:
   	<fann_set_activation_steepness_layer>, <fann_set_activation_steepness_hidden>,
   	<fann_set_activation_steepness_output>, <fann_set_activation_function>,
    <fann_get_activation_steepness>

   This function appears in FANN >= 2.0.0.
 */ 
FANN_EXTERNAL void FANN_API fann_set_activation_steepness(struct fann *ann,
																fann_type steepness,
																int layer,
																int neuron);

/* Function: fann_set_activation_steepness_layer

   Set the activation steepness all of the neurons in layer number *layer*, 
   counting the input layer as layer 0. 
   
   It is not possible to set activation steepness for the neurons in the input layer.
   
   See also:
   	<fann_set_activation_steepness>, <fann_set_activation_steepness_hidden>,
   	<fann_set_activation_steepness_output>, <fann_set_activation_function_layer>

   This function appears in FANN >= 2.0.0.
 */ 
FANN_EXTERNAL void FANN_API fann_set_activation_steepness_layer(struct fann *ann,
																fann_type steepness,
																int layer);

/* Function: fann_set_activation_steepness_hidden

   Set the steepness of the activation steepness in all of the hidden layers.

   See also:
   	<fann_set_activation_steepness>, <fann_set_activation_steepness_layer>,
   	<fann_set_activation_steepness_output>, <fann_set_activation_function_hidden>

   This function appears in FANN >= 1.2.0.
 */ 
FANN_EXTERNAL void FANN_API fann_set_activation_steepness_hidden(struct fann *ann,
																 fann_type steepness);


/* Function: fann_set_activation_steepness_output

   Set the steepness of the activation steepness in the output layer.

   See also:
   	<fann_set_activation_steepness>, <fann_set_activation_steepness_layer>,
   	<fann_set_activation_steepness_hidden>, <fann_set_activation_function_output>

   This function appears in FANN >= 1.2.0.
 */ 
FANN_EXTERNAL void FANN_API fann_set_activation_steepness_output(struct fann *ann,
																 fann_type steepness);


/* Function: fann_get_train_error_function

   Returns the error function used during training.

   The error functions is described further in <fann_errorfunc_enum>
   
   The default error function is FANN_ERRORFUNC_TANH
   
   See also:
   	<fann_set_train_error_function>
      
   This function appears in FANN >= 1.2.0.
  */ 
FANN_EXTERNAL enum fann_errorfunc_enum FANN_API fann_get_train_error_function(struct fann *ann);


/* Function: fann_set_train_error_function

   Set the error function used during training.
   
   The error functions is described further in <fann_errorfunc_enum>
   
   See also:
   	<fann_get_train_error_function>
      
   This function appears in FANN >= 1.2.0.
 */ 
FANN_EXTERNAL void FANN_API fann_set_train_error_function(struct fann *ann,
														  enum fann_errorfunc_enum 
														  train_error_function);


/* Function: fann_get_train_stop_function

   Returns the the stop function used during training.
   
   The stop function is described further in <fann_stopfunc_enum>
   
   The default stop function is FANN_STOPFUNC_MSE
   
   See also:
   	<fann_get_train_stop_function>, <fann_get_bit_fail_limit>
      
   This function appears in FANN >= 2.0.0.
 */ 
FANN_EXTERNAL enum fann_stopfunc_enum FANN_API fann_get_train_stop_function(struct fann *ann);


/* Function: fann_set_train_stop_function

   Set the stop function used during training.

   Returns the the stop function used during training.
   
   The stop function is described further in <fann_stopfunc_enum>
   
   See also:
   	<fann_get_train_stop_function>
      
   This function appears in FANN >= 2.0.0.
 */ 
FANN_EXTERNAL void FANN_API fann_set_train_stop_function(struct fann *ann,
														 enum fann_stopfunc_enum train_stop_function);


/* Function: fann_get_bit_fail_limit

   Returns the bit fail limit used during training.
   
   The bit fail limit is used during training where the <fann_stopfunc_enum> is set to FANN_STOPFUNC_BIT.

   The limit is the maximum accepted difference between the desired output and the actual output during
   training. Each output that diverges more than this limit is counted as an error bit.
   This difference is divided by two when dealing with symmetric activation functions,
   so that symmetric and not symmetric activation functions can use the same limit.
   
   The default bit fail limit is 0.35.
   
   See also:
   	<fann_set_bit_fail_limit>
   
   This function appears in FANN >= 2.0.0.
 */ 
FANN_EXTERNAL fann_type FANN_API fann_get_bit_fail_limit(struct fann *ann);

/* Function: fann_set_bit_fail_limit

   Set the bit fail limit used during training.
  
   See also:
   	<fann_get_bit_fail_limit>
   
   This function appears in FANN >= 2.0.0.
 */ 
FANN_EXTERNAL void FANN_API fann_set_bit_fail_limit(struct fann *ann, fann_type bit_fail_limit);

/* Function: fann_set_callback
   
   Sets the callback function for use during training.
 	
   See <fann_callback_type> for more information about the callback function.
   
   The default callback function simply prints out some status information.

   This function appears in FANN >= 2.0.0.
 */
FANN_EXTERNAL void FANN_API fann_set_callback(struct fann *ann, fann_callback_type callback);

/* Function: fann_get_quickprop_decay

   The decay is a small negative valued number which is the factor that the weights 
   should become smaller in each iteration during quickprop training. This is used 
   to make sure that the weights do not become too high during training.
   
   The default decay is -0.0001.
   
   See also:
   	<fann_set_quickprop_decay>

   This function appears in FANN >= 1.2.0.
 */
FANN_EXTERNAL float FANN_API fann_get_quickprop_decay(struct fann *ann);


/* Function: fann_set_quickprop_decay
   
   Sets the quickprop decay factor.
   
   See also:
   	<fann_get_quickprop_decay>

   This function appears in FANN >= 1.2.0.
*/ 
FANN_EXTERNAL void FANN_API fann_set_quickprop_decay(struct fann *ann, float quickprop_decay);


/* Function: fann_get_quickprop_mu

   The mu factor is used to increase and decrease the step-size during quickprop training. 
   The mu factor should always be above 1, since it would otherwise decrease the step-size 
   when it was suppose to increase it.
   
   The default mu factor is 1.75. 
   
   See also:
   	<fann_set_quickprop_mu>

   This function appears in FANN >= 1.2.0.
*/ 
FANN_EXTERNAL float FANN_API fann_get_quickprop_mu(struct fann *ann);


/* Function: fann_set_quickprop_mu

    Sets the quickprop mu factor.
   
   See also:
   	<fann_get_quickprop_mu>

   This function appears in FANN >= 1.2.0.
*/ 
FANN_EXTERNAL void FANN_API fann_set_quickprop_mu(struct fann *ann, float quickprop_mu);


/* Function: fann_get_rprop_increase_factor

   The increase factor is a value larger than 1, which is used to 
   increase the step-size during RPROP training.

   The default increase factor is 1.2.
   
   See also:
   	<fann_set_rprop_increase_factor>

   This function appears in FANN >= 1.2.0.
*/ 
FANN_EXTERNAL float FANN_API fann_get_rprop_increase_factor(struct fann *ann);


/* Function: fann_set_rprop_increase_factor

   The increase factor used during RPROP training.

   See also:
   	<fann_get_rprop_increase_factor>

   This function appears in FANN >= 1.2.0.
*/ 
FANN_EXTERNAL void FANN_API fann_set_rprop_increase_factor(struct fann *ann,
														   float rprop_increase_factor);


/* Function: fann_get_rprop_decrease_factor

   The decrease factor is a value smaller than 1, which is used to decrease the step-size during RPROP training.

   The default decrease factor is 0.5.

   See also:
    <fann_set_rprop_decrease_factor>

   This function appears in FANN >= 1.2.0.
*/ 
FANN_EXTERNAL float FANN_API fann_get_rprop_decrease_factor(struct fann *ann);


/* Function: fann_set_rprop_decrease_factor

   The decrease factor is a value smaller than 1, which is used to decrease the step-size during RPROP training.

   See also:
    <fann_get_rprop_decrease_factor>

   This function appears in FANN >= 1.2.0.
*/
FANN_EXTERNAL void FANN_API fann_set_rprop_decrease_factor(struct fann *ann,
														   float rprop_decrease_factor);


/* Function: fann_get_rprop_delta_min

   The minimum step-size is a small positive number determining how small the minimum step-size may be.

   The default value delta min is 0.0.

   See also:
   	<fann_set_rprop_delta_min>
   	
   This function appears in FANN >= 1.2.0.
*/ 
FANN_EXTERNAL float FANN_API fann_get_rprop_delta_min(struct fann *ann);


/* Function: fann_set_rprop_delta_min

   The minimum step-size is a small positive number determining how small the minimum step-size may be.

   See also:
   	<fann_get_rprop_delta_min>
   	
   This function appears in FANN >= 1.2.0.
*/ 
FANN_EXTERNAL void FANN_API fann_set_rprop_delta_min(struct fann *ann, float rprop_delta_min);


/* Function: fann_get_rprop_delta_max

   The maximum step-size is a positive number determining how large the maximum step-size may be.

   The default delta max is 50.0.

   See also:
   	<fann_set_rprop_delta_max>, <fann_get_rprop_delta_min>

   This function appears in FANN >= 1.2.0.
*/ 
FANN_EXTERNAL float FANN_API fann_get_rprop_delta_max(struct fann *ann);


/* Function: fann_set_rprop_delta_max

   The maximum step-size is a positive number determining how large the maximum step-size may be.

   See also:
   	<fann_get_rprop_delta_max>, <fann_get_rprop_delta_min>

   This function appears in FANN >= 1.2.0.
*/
FANN_EXTERNAL void FANN_API fann_set_rprop_delta_max(struct fann *ann, float rprop_delta_max);

#endif