[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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