Home/ Questions/Error: error in neurons[[i]] %*% weights[[i]] : requires numeric/complex matrix/vector arguments - how to solve it?
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Helena Martin
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Asked: 2022-05-18T19:01:42+00:00 In:

Error: error in neurons[[i]] %*% weights[[i]] : requires numeric/complex matrix/vector arguments – how to solve it?

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Hi developer experts, I have a small but frustrating use case, and so far, I couldn’t get my head around this problem & ideal solution. I am running my command and facing one problem with the error in neurons[[i]] %*% weights[[i]] : requires numeric/complex matrix/vector arguments. Below is the command I used:

- survived: 1
 - pclass: 3
 - sex: male
 - age: 22.0
 - sibsp: 1
 - parch: 0
 - ticket: PC 17601
 - fare: 7.25
 - cabin: C85
 - embarked: S
> net <- neuralnet(survived ~ pclass + sex + age + sibsp +
  parch + ticket + fare + cabin + embarked, 
  train, hidden=10, threshold=0.01)

When I run it, I get the following error:

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

I am looking forward to gaining some knowledge from all experts. Thank you, guys!

regression
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2 Answers

  1. Best Answer
    Expert

    The cause: You can eliminate the name, ticket, cabin, and passengerId variables because they have too many values to be relevant (at least in your initial model).

    Solution:

    If it makes more sense, you might also want to convert some of the numerical variables (like class) to factors. The model.matrix function can be used to convert all qualitative variables (factors) to binary (“dummy”) variables because neuralnet only works with quantitative variables.

    m <- model.matrix(
~ Survived + Pclass + Sex + Age + SibSp + Parch + Fare + Embarked,
data = d
)
head(m)
library(neuralnet)
r <- neuralnet(
Survived ~ Pclass + Sexmale + Age + SibSp + Parch + Fare + EmbarkedC + EmbarkedQ + EmbarkedS,
data=m, hidden=10, threshold=0.01
)

     

    • 0

  2. When you have character or factor variables in your data, an error message “requis numeric/complex matrix/vector arguments” will occur.

    This problem can be solved in three ways:

    1. Remove the variable
    2. Use integer instead if the variable is an ordinal factor.
    3. If the variable is character then transform it into factor, and then into a dummy variable.

    To convert a factor into a dummy variable, you can use either model.matrix() or class.ind() functions from the nnet package.

    • 10

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