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DBN+BPNN for fault classification #182
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You can try to change the initial weight of the RBM and increase the number of training. |
@joey0111 |
A random number between 0 and 1 is not enough. You can try multiplying all the initial weights by 0.01 or a smaller number. Also, have you normalized the input data? |
@joey0111 |
Have you solved this problem? It seems that I have come across the same question. |
i use the new matlab2018b。
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Eric
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lq283528870@163.com
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签名由网易邮箱大师定制
On 4/26/2019 15:07,Yunlong Wang<notifications@github.com> wrote:
Have you solved this problem? It seems that I have come across the same question.
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I hava tried to use matlab2018b,but the result doesn't change at all.Is it possible that the code has a problem?
…------------------ 原始邮件 ------------------
发件人: "Yi Jing"<notifications@github.com>;
发送时间: 2019年4月26日(星期五) 下午3:44
收件人: "rasmusbergpalm/DeepLearnToolbox"<DeepLearnToolbox@noreply.github.com>;
抄送: "王云龙"<1922631820@qq.com>; "Comment"<comment@noreply.github.com>;
主题: Re: [rasmusbergpalm/DeepLearnToolbox] DBN+BPNN for faultclassification (#182)
i use the new matlab2018b。
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Eric
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lq283528870@163.com
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签名由网易邮箱大师定制
On 4/26/2019 15:07,Yunlong Wang<notifications@github.com> wrote:
Have you solved this problem? It seems that I have come across the same question.
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You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub, or mute the thread.
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You are receiving this because you commented.
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这个工具箱是没有问题的,就是不好调试,因为需要人工进行。 我用自己的数据,总共十类,用这个工具箱可以达到95的准确率。 |
I use DBN for the classification of bearing fault data sets at Case Western Reserve University. The data set includes 10 failures, but the final classification result is always a category. When you modify various parameters of the network in nnsetup.m, the result will change accordingly. For example, when you change nn.learningrate to 1, the classification will change from 1 to 4. Many people have encountered this problem, but No suitable solution was found. Sincere hope that someone can help me
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