get_params_class_mlpT_get_params_class_mlpGetParamsClassMlpGetParamsClassMlpget_params_class_mlp (Operator)
get_params_class_mlpT_get_params_class_mlpGetParamsClassMlpGetParamsClassMlpget_params_class_mlp — Return the parameters of a multilayer perceptron.
Signature
void GetParamsClassMlp(const HTuple& MLPHandle, HTuple* NumInput, HTuple* NumHidden, HTuple* NumOutput, HTuple* OutputFunction, HTuple* Preprocessing, HTuple* NumComponents)
Hlong HClassMlp::GetParamsClassMlp(Hlong* NumHidden, Hlong* NumOutput, HString* OutputFunction, HString* Preprocessing, Hlong* NumComponents) const
static void HOperatorSet.GetParamsClassMlp(HTuple MLPHandle, out HTuple numInput, out HTuple numHidden, out HTuple numOutput, out HTuple outputFunction, out HTuple preprocessing, out HTuple numComponents)
int HClassMlp.GetParamsClassMlp(out int numHidden, out int numOutput, out string outputFunction, out string preprocessing, out int numComponents)
def get_params_class_mlp(mlphandle: HHandle) -> Tuple[int, int, int, str, str, int]
Description
get_params_class_mlpget_params_class_mlpGetParamsClassMlpGetParamsClassMlpget_params_class_mlp returns the parameters of a multilayer
perceptron (MLP) that were specified when the MLP was created with
create_class_mlpcreate_class_mlpCreateClassMlpCreateClassMlpcreate_class_mlp. This is particularly useful if the MLP
was read from a file with read_class_mlpread_class_mlpReadClassMlpReadClassMlpread_class_mlp. The output of
get_params_class_mlpget_params_class_mlpGetParamsClassMlpGetParamsClassMlpget_params_class_mlp can, for example, be used to check
whether the feature vectors and, if necessary, the target data to be
used with the MLP have the correct lengths. For a description of
the parameters, see create_class_mlpcreate_class_mlpCreateClassMlpCreateClassMlpcreate_class_mlp.
Execution Information
- Multithreading type: reentrant (runs in parallel with non-exclusive operators).
- Multithreading scope: global (may be called from any thread).
- Processed without parallelization.
Parameters
MLPHandleMLPHandleMLPHandleMLPHandlemlphandle (input_control) class_mlp → HClassMlp, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)
MLP handle.
NumInputNumInputNumInputnumInputnum_input (output_control) integer → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)
Number of input variables (features) of the MLP.
NumHiddenNumHiddenNumHiddennumHiddennum_hidden (output_control) integer → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)
Number of hidden units of the MLP.
NumOutputNumOutputNumOutputnumOutputnum_output (output_control) integer → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)
Number of output variables (classes) of the MLP.
OutputFunctionOutputFunctionOutputFunctionoutputFunctionoutput_function (output_control) string → HTuplestrHTupleHtuple (string) (string) (HString) (char*)
Type of the activation function in the output
layer of the MLP.
PreprocessingPreprocessingPreprocessingpreprocessingpreprocessing (output_control) string → HTuplestrHTupleHtuple (string) (string) (HString) (char*)
Type of preprocessing used to transform the
feature vectors.
NumComponentsNumComponentsNumComponentsnumComponentsnum_components (output_control) integer → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)
Preprocessing parameter: Number of transformed
features.
Result
If the parameters are valid, the operator
get_params_class_mlpget_params_class_mlpGetParamsClassMlpGetParamsClassMlpget_params_class_mlp returns the value 2 (
H_MSG_TRUE)
. If necessary,
an exception is raised.
Possible Predecessors
create_class_mlpcreate_class_mlpCreateClassMlpCreateClassMlpcreate_class_mlp,
read_class_mlpread_class_mlpReadClassMlpReadClassMlpread_class_mlp
Possible Successors
add_sample_class_mlpadd_sample_class_mlpAddSampleClassMlpAddSampleClassMlpadd_sample_class_mlp,
train_class_mlptrain_class_mlpTrainClassMlpTrainClassMlptrain_class_mlp
See also
evaluate_class_mlpevaluate_class_mlpEvaluateClassMlpEvaluateClassMlpevaluate_class_mlp,
classify_class_mlpclassify_class_mlpClassifyClassMlpClassifyClassMlpclassify_class_mlp
Module
Foundation