我们可以把loss的function写出来,这个loss的function 这个L是 正确答案 ŷ减掉model的输出,也就是w₁ w₂x,这边取square error,这边只有一笔data,所以就不会summation over所有的training data,因為反正只有一笔data,x代1 ŷ代1,我刚才说过只有一笔训练资料最废的,所以只有一笔训练资料,所以loss funct...
也就是w₁ w₂x,这边取square error,这边只有一笔data,所以就不会summation over所有的training data,因為反正只有一笔data,x代1 ŷ代1,我刚才说过只有一笔训练资料最废的,所以只有一笔训练资料,所以loss function就是$L=(\hat{y}-w_1 w_2 ...
Kernel risk sensitive mean p-power lossExcess mean square errorsRandom-Fourier-featuresRobustnessThe least mean square (LMS) algorithm is optimal for combating Gaussian noises owing to the used minimum mean square error (MSE) criterion in its loss function. However, the MSE criterion is not ...
The criterion of asymptotic sufficiency which has been called "second order efficiency" is rejected as a criterion of goodness of estimate as against some loss function such as the mean squared error. The relation between MLE and sufficiency is not assured, as illustrated in an example in which...
loss = F.sum(loss)returnloss 开发者ID:Bartzi,项目名称:kiss,代码行数:21,代码来源:utils.py 示例4: reshape_to_yolo_size ▲点赞 6▼ # 需要导入模块: from chainer import functions [as 别名]# 或者: from chainer.functions importminimum[as 别名]defreshape_to_yolo_size(img):input_height, inpu...
measure the accuracy of a particular candidate. The most common choice is the minimum mean-square error (MMSE) criterion which is also the conditional expectation of the unknown quantity.For a discussion of alternative loss funct 要构想优选的预言或提取的理论要求测量一名特殊候选人的准确性的某一标准...
Minimum Classification Error (MCE) training, which has been widely used as one of the recent standards of discriminative training for classifiers, is characterized by a smooth sigmoidal-form classification error count loss. The smoothness of this loss function effectively increases training robustness to...
value_function_loss = tf.losses.mean_squared_error( q_n - self._alpha * log_pis, v_n )returnvalue_function_loss 开发者ID:xuwd11,项目名称:cs294-112_hws,代码行数:19,代码来源:sac.py 示例7: padded_accuracy_topk ▲点赞 6▼ # 需要导入模块: import tensorflow [as 别名]# 或者: from te...
The user selectable functions include the remaining functions of LAP-D, i.e., error recovery through acknowledgments as well as retransmission and flow control through windowing. A summary of these function can be seen in Fig. 15. Sign in to download full-size image Figure 15. Segregation of...
delta: `float`, the point where the huber loss function changes from a quadratic to linear. scope: The scope for the operations performed in computing the loss. loss_collection: collection to which the loss will be added. reduction: Type of reduction to apply to loss. ...