evaluate_class_mlpT_evaluate_class_mlpEvaluateClassMlpEvaluateClassMlpevaluate_class_mlp (算子名称)

名称

evaluate_class_mlpT_evaluate_class_mlpEvaluateClassMlpEvaluateClassMlpevaluate_class_mlp — Calculate the evaluation of a feature vector by a multilayer perceptron.

参数签名

描述

evaluate_class_mlpevaluate_class_mlpEvaluateClassMlpEvaluateClassMlpEvaluateClassMlpevaluate_class_mlp computes the result ResultResultResultResultresultresult of evaluating the feature vector 特征特征特征特征特征特征 with the multilayer perceptron (MLP) MLPHandleMLPHandleMLPHandleMLPHandleMLPHandlemlphandle. The formulas used for the evaluation are described with create_class_mlpcreate_class_mlpCreateClassMlpCreateClassMlpCreateClassMlpcreate_class_mlp. Before calling evaluate_class_mlpevaluate_class_mlpEvaluateClassMlpEvaluateClassMlpEvaluateClassMlpevaluate_class_mlp, the MLP must be trained with train_class_mlptrain_class_mlpTrainClassMlpTrainClassMlpTrainClassMlptrain_class_mlp.

If the MLP is used for regression (function approximation), i.e., if (OutputFunctionOutputFunctionOutputFunctionOutputFunctionoutputFunctionoutput_function = 'linear'"linear""linear""linear""linear""linear"), ResultResultResultResultresultresult is the value of the function at the coordinate 特征特征特征特征特征特征. For OutputFunctionOutputFunctionOutputFunctionOutputFunctionoutputFunctionoutput_function = 'logistic'"logistic""logistic""logistic""logistic""logistic" and 'softmax'"softmax""softmax""softmax""softmax""softmax", the values in ResultResultResultResultresultresult can be interpreted as probabilities. Hence, for OutputFunctionOutputFunctionOutputFunctionOutputFunctionoutputFunctionoutput_function = 'logistic'"logistic""logistic""logistic""logistic""logistic" the elements of ResultResultResultResultresultresult represent the probabilities of the presence of the respective independent attributes. Typically, a threshold of 0.5 is used to decide whether the attribute is present or not. Depending on the application, other thresholds may be used as well. For OutputFunctionOutputFunctionOutputFunctionOutputFunctionoutputFunctionoutput_function = 'softmax'"softmax""softmax""softmax""softmax""softmax" usually the position of the maximum value of ResultResultResultResultresultresult is interpreted as the class of the feature vector, and the corresponding value as the probability of the class. In this case, classify_class_mlpclassify_class_mlpClassifyClassMlpClassifyClassMlpClassifyClassMlpclassify_class_mlp should be used instead of evaluate_class_mlpevaluate_class_mlpEvaluateClassMlpEvaluateClassMlpEvaluateClassMlpevaluate_class_mlp because classify_class_mlpclassify_class_mlpClassifyClassMlpClassifyClassMlpClassifyClassMlpclassify_class_mlp directly returns the class and corresponding probability.

运行信息

• 多线程类型:可重入(与非独占操作符并行运行)。
• 多线程作用域:全局(可以从任何线程调用)。
• 未经并行化处理。

参数表

结果

如果参数均有效，算子 evaluate_class_mlpevaluate_class_mlpEvaluateClassMlpEvaluateClassMlpEvaluateClassMlpevaluate_class_mlp 返回值 2 ( H_MSG_TRUE) . If necessary, an exception is raised.

可能的前置算子

train_class_mlptrain_class_mlpTrainClassMlpTrainClassMlpTrainClassMlptrain_class_mlp, read_class_mlpread_class_mlpReadClassMlpReadClassMlpReadClassMlpread_class_mlp

可替代算子

classify_class_mlpclassify_class_mlpClassifyClassMlpClassifyClassMlpClassifyClassMlpclassify_class_mlp

参考其它

create_class_mlpcreate_class_mlpCreateClassMlpCreateClassMlpCreateClassMlpcreate_class_mlp

References

Christopher M. Bishop: “Neural Networks for Pattern Recognition”; Oxford University Press, Oxford; 1995.
Andrew Webb: “Statistical Pattern Recognition”; Arnold, London; 1999.

模块

Foundation

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