R NeuroNet:“不一致的参数". [英] R neuralNet: "non-conformable arguments"

问题描述

啊！尝试使用神经网络compute时，始终出现以下错误:

Argh! I keep getting the following error when attempting to compute with my neural network:

> net.compute <- compute(net, matrix.train2)
Error in neurons[[i]] %*% weights[[i]] : non-conformable arguments

我不知道是什么问题.下面，我将为您提供示例数据和矩阵格式的示例，然后向您展示我尝试运行的代码.

I can't figure out what the problem is. Below I'll provide you with an example data and formatting from my matrices and then I'll show you the code I'm attempting to run.

• matrix.train1用于训练网络

> matrix.train1
    (Intercept) survived pclass sexmale    age sibsp parch     fare embarkedC embarkedQ embarkedS
1             1        0      3       1  22.00     1     0   7.2500         0         0             1
2             1        1      1       0  38.00     1     0  71.2833         1         0         0
3             1        1      3       0  26.00     0     0   7.9250         0         0         1
4             1        1      1       0  35.00     1     0  53.1000         0         0         1
5             1        0      3       1  35.00     0     0   8.0500         0         0         1
6             1        0      3       1 999.00     0     0   8.4583         0         1         0
7             1        0      1       1  54.00     0     0  51.8625         0         0         1
8             1        0      3       1   2.00     3     1  21.0750         0         0         1
9             1        1      3       0  27.00     0     2  11.1333         0         0         1
10            1        1      2       0  14.00     1     0  30.0708         1         0         0
11            1        1      3       0   4.00     1     1  16.7000         0         0         1

matrix.train2是用于测试模型的训练数据的一部分

matrix.train2 is a slice of the training data used for testing the model

> matrix.train2
    (Intercept) pclass sexmale    age sibsp parch     fare embarkedC embarkedQ embarkedS
1             1      1       1  49.00     1     1 110.8833         1         0         0
2             1      3       1  42.00     0     0   7.6500         0         0         1
3             1      1       0  18.00     1     0 227.5250         1         0         0
4             1      1       1  35.00     0     0  26.2875         0         0         1
5             1      3       0  18.00     0     1  14.4542         1         0         0
6             1      3       1  25.00     0     0   7.7417         0         1         0
7             1      3       1  26.00     1     0   7.8542         0         0         1
8             1      2       1  39.00     0     0  26.0000         0         0         1
9             1      2       0  45.00     0     0  13.5000         0         0         1
10            1      1       1  42.00     0     0  26.2875         0         0         1
11            1      1       0  22.00     0     0 151.5500         0         0         1

两个矩阵之间唯一的真正区别是matrix.train2不包含survived列.

The only real difference between the two matrices is that matrix.train2 doesn't contain the survived column.

这是我正在尝试运行的R代码:

Here's the R code I'm attempting to run:

#Build a matrix from training data 
matrix.train1 <- model.matrix(
  ~ survived + pclass + sex + age + sibsp + parch + fare + embarked, 
  data=train1
)

library(neuralnet)

#Train the neural net
net <- neuralnet(
  survived ~ pclass + sexmale + age + sibsp + parch + fare + embarkedC + 
  embarkedQ + embarkedS, data=matrix.train1, hidden=10, threshold=0.01
)

#Build a matrix from test data
matrix.train2 <- model.matrix(
  ~ pclass + sex + age + sibsp + parch + fare + embarked, 
  data=train2
)

#Apply neural net to test matrix 
net.results <- compute(
  net, matrix.train2
)

Error in neurons[[i]] %*% weights[[i]] : non-conformable arguments

有人可以告诉我我在做什么错吗?

Can anyone tell me what I'm doing wrong here?

谢谢！

根据到目前为止的评论进行更新:

Updates based on comments so far:

1. 使用来自"> 新的预测类的解决方案使用Neuronet 的数据似乎无效.

1. Using the solution from "Predicting class for new data using neuralnet" doesn't seem to work.

> net.compute <- compute(net, matrix.train2[,1:10])
Error in neurons[[i]] %*% weights[[i]] : non-conformable arguments

我正在通过model.matrix手动将train1和train2数据帧放入矩阵，因为如果没有，则会出现以下错误:

I'm manually putting my train1 and train2 data frames into matrices via model.matrix because if I don't I get the following error:

> Error in neurons[[i]] %*% weights[[i]] : 
requires numeric/complex matrix/vector arguments

注意:有关为什么使用model.matrix的更多详细信息，请参见以下线程:" ".

Note: see the following thread for more details on why I'm using model.matrix: "Working with neuralnet in R for the first time: get "requires numeric/complex matrix/vector arguments" but don't know how to correct".

推荐答案

您似乎需要删除预测变量.试试这个:

It looks like you need to remove the predictor variable. Try this:

nn_pred<-compute(nn,test[,3:11])

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