get_params_class_mlpT_get_params_class_mlpGetParamsClassMlpGetParamsClassMlpget_params_class_mlp (算子名称)
名称
get_params_class_mlpT_get_params_class_mlpGetParamsClassMlpGetParamsClassMlpget_params_class_mlp — Return the parameters of a multilayer perceptron.
参数签名
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]
描述
get_params_class_mlpget_params_class_mlpGetParamsClassMlpGetParamsClassMlpGetParamsClassMlpget_params_class_mlp returns the parameters of a multilayer
perceptron (MLP) that were specified when the MLP was created with
create_class_mlpcreate_class_mlpCreateClassMlpCreateClassMlpCreateClassMlpcreate_class_mlp. This is particularly useful if the MLP
was read from a file with read_class_mlpread_class_mlpReadClassMlpReadClassMlpReadClassMlpread_class_mlp. The output of
get_params_class_mlpget_params_class_mlpGetParamsClassMlpGetParamsClassMlpGetParamsClassMlpget_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_mlpCreateClassMlpCreateClassMlpCreateClassMlpcreate_class_mlp.
运行信息
- Multithreading type: reentrant (runs in parallel with non-exclusive operators).
- Multithreading scope: global (may be called from any thread).
- Processed without parallelization.
参数表
MLPHandleMLPHandleMLPHandleMLPHandleMLPHandlemlphandle (input_control) class_mlp → HClassMlp, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)
MLP handle.
NumInputNumInputNumInputNumInputnumInputnum_input (output_control) integer → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)
Number of input variables (features) of the MLP.
NumHiddenNumHiddenNumHiddenNumHiddennumHiddennum_hidden (output_control) integer → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)
Number of hidden units of the MLP.
NumOutputNumOutputNumOutputNumOutputnumOutputnum_output (output_control) integer → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)
Number of output variables (classes) of the MLP.
OutputFunctionOutputFunctionOutputFunctionOutputFunctionoutputFunctionoutput_function (output_control) string → HTuplestrHTupleHtuple (string) (string) (HString) (char*)
Type of the activation function in the output
layer of the MLP.
PreprocessingPreprocessingPreprocessingPreprocessingpreprocessingpreprocessing (output_control) string → HTuplestrHTupleHtuple (string) (string) (HString) (char*)
Type of preprocessing used to transform the
feature vectors.
NumComponentsNumComponentsNumComponentsNumComponentsnumComponentsnum_components (output_control) integer → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)
Preprocessing parameter: Number of transformed
features.
结果
If the parameters are valid, the operator
get_params_class_mlpget_params_class_mlpGetParamsClassMlpGetParamsClassMlpGetParamsClassMlpget_params_class_mlp returns the value 2 (
H_MSG_TRUE)
. If necessary,
an exception is raised.
可能的前置算子
create_class_mlpcreate_class_mlpCreateClassMlpCreateClassMlpCreateClassMlpcreate_class_mlp,
read_class_mlpread_class_mlpReadClassMlpReadClassMlpReadClassMlpread_class_mlp
可能的后置算子
add_sample_class_mlpadd_sample_class_mlpAddSampleClassMlpAddSampleClassMlpAddSampleClassMlpadd_sample_class_mlp,
train_class_mlptrain_class_mlpTrainClassMlpTrainClassMlpTrainClassMlptrain_class_mlp
参考其它
evaluate_class_mlpevaluate_class_mlpEvaluateClassMlpEvaluateClassMlpEvaluateClassMlpevaluate_class_mlp,
classify_class_mlpclassify_class_mlpClassifyClassMlpClassifyClassMlpClassifyClassMlpclassify_class_mlp
模块
Foundation