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你好,很抱歉,又来打扰。 看到你把源域和辅域权重的更新又修改为戴文渊paper中提到的更新方式,我想冒昧的问一下,你是在哪些数据集上做的验证证明戴的方法是可以收敛的? 我怎么是在你之前提到的权重更新方式下才能收敛,戴的方法不能收敛呢?
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我也是这个问题,两种权重我都实验了,第一次迭代就error rate就等于0,实际test并不好,求教该什么原因,负迁移么?
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@vilin777 @zhangjiantianyasmile 我也遇到了这个问题, 按照icml 2007上面tradaboost的权重更新方法复现了只有数值型特征的mushroom数据集上的实验,是无法收敛的,加权错误率始终在0.5左右。而按照作者更改之前的tradaboost更新方法(即beta_t是1,beta是-1),实验反而收敛了。。很奇怪
第一次迭代error rate就等于0是因为决策树函数的问题,希望能对大家有帮助,需要设置max_depth, min_samples_leaf这两个参数哈,具体见最新的那个issue。
@MrDavidG 你好,请问 作者更改之前的tradaboost更新方法(即beta_t是1,beta是-1) 具体是怎么更新的呢?我目前也在使用tradaboost做训练。谢谢
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你好,很抱歉,又来打扰。
看到你把源域和辅域权重的更新又修改为戴文渊paper中提到的更新方式,我想冒昧的问一下,你是在哪些数据集上做的验证证明戴的方法是可以收敛的?
我怎么是在你之前提到的权重更新方式下才能收敛,戴的方法不能收敛呢?
The text was updated successfully, but these errors were encountered: