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学习率不影响我在 R 中的人工神经网络

[英]Learning rate is not affecting my artificial neural network in R

I have the following model to predict the price of houses in a particular neighborhood:我有以下 model 来预测特定社区的房价:

set.seed(100)
index_1<-sample(1:nrow(data),round(nrow(data)*0.9))
train<-data[index_1,] #578 obs.
test<-data[-index_1,] #62 obs.

NModel <- neuralnet(price ~  x1 + x2 + x3 + x4, data=train_group, hidden=c(5), linear.output=FALSE, threshold =0.01, rep=20, learningrate = 0.25 )

However I have been changing my learning rate from 0.25 to 1 and nothing has changed on my RMSE.但是,我一直在将学习率从 0.25 更改为 1,而我的 RMSE 没有任何变化。 It neither gets worse nor gets better, it stays exactly the same, even when changing a learning rate.它既不会变得更糟也不会变得更好,它保持完全相同,即使在改变学习率时也是如此。 Does anyone have any hints of what may be happening?有人对可能发生的事情有任何暗示吗?

neuralnet function | 神经网络 function | R Documentation R 文档

learningrate is used only for traditional backpropagation. learningrate仅用于传统的反向传播。 Try adding the argument algorithm = 'backprop' and then see what different values for learningrate do.尝试添加参数algorithm = 'backprop'然后查看learningrate的不同值。

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