size_average=None,reduce=None,reduction='mean'):super(MultiLabelMarginLoss,self).__init__(size_average,reduce,reduction)defforward(self,input,target):returnF.multilabel_margin_loss(input,target,reduction=self.reduction)
2.1 背景/问题 在多标签分类任务中,平均来看1张图片只有很少的positive label而有较多的negative label,导致训练过程中对positive label的关注较少 2.2 研究内容 提出asymmetric loss(ASL),动态地对easy negative进行down-weight(soft-threshold)和hard-threshold 3 Asymmetric Loss ...
难样本挖掘 WSDM-2021-DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents 在XMC场景下,每个样本的大部分标签是未激活的。因而如果使用全部的样本-标签对进行训练会导致复杂度过高,同时由于负样本过多会导致严重的不均衡问题。 通过负采样获取少量负样本,降低模型复杂度,加快模...
1、一般直接用损失函数(log_loss、 zero_one_loss、hinge_loss)就可以,但针对样本不均衡的情况,只用正确率不够,2、两类分类任务中更多评价指标:ROC/AUC、PR曲线、AP,3、多类分类(multi-class) and 多标签分类(mulit-label) and 多输出-多分类-多标签classification评价指标 1、损失函数 log_loss:负log似然损...
loss(x,y)=1C∑iCmax(0,margin−x[i]+x[y])p loss(x,y) = \frac{1}{C}\sum_i^C max(0, margin-x[i]+x[y])^p loss(x,y)=C1∑iCmax(0,margin−x[i]+x[y])p 其中CCC 为类别数。若 batch_size 为 1 时,xxx 是一个(C,)的 input,yyy 是一个标量的 label (0≤y≤C−10...
asweshowinSection3,thehingelossfunctionusedin Westonetal.[32]andGongetal.[9]isnon-smoothand 3617 thusisdifficulttooptimize.Second,therankingobjective2.RelatedWork doesnotfullyoptimizethemulti-labelobjective. Multi-labelclassificationisalong-standingproblemthat ...
The standard way to train a multilabel classifier is with sigmoid + binary_crossentropy, but you can train a multilabel classifier with tanh + hinge, just the targets should be in {-1,1}. I don't think your issue has to do with the loss and the output activation, I think is more...
Finally, the third block consists of an output layer that adapts the second block's outputs to the label space. We propose a backpropagation learning algorithm that uses a squared hinge loss function to maximize the margins between labels to train this network. The results show that our model...
the hinge loss function is replaced with the pinball loss which will make it less sensitive to the noise points. Furthermore, to speed up pin-ENR, a safe simultaneousfeature andlabel-paireliminationrule, termed as FLER-pin-ENR, is constructed based on the strong convexity of the primal and ...
However, due to the use of square hinge loss, LM-kNN needs to iteratively solve a constrained quadratic programming at a high computational cost. To address this issue, we propose a novel metric learning-guided k nearest neighbor approach (MLG-kNN) for multilabel classification. Specifically, ...