为什么是我的neuralnet功能的工作不在我的计划？

Question 1

我得到了错误 Error in eval(predvars, data, env) : object 'B' not found我不知道该如何做到这一行：

nn <- neuralnet(B+M~ area+texture+smoothness, data=cancertrain, hidden=3,

B+M是两个潜在价值，无论是良性或恶性肿瘤，并在三个属性，具有更大的影响，在确定区域、质地和平稳性。我假设我只有参数的功能neuralnet做得不正确，任何人都不会知道？这就是癌症的数据集中在一个公共谷歌的电子表格。

library(neuralnet)
library(ISLR) 
library(rpart)
library(rpart.plot)
library(caTools)
library(random)

#setwd("**change to your working directory**")
data <- read.csv("WDBC.csv", header=T)
#head(data)

cancer.dataset <- data
  
#according to previous models and studies, area, texture, and smoothness are the
#attributes with the highest relevance to the diagnosis of benign or malignant
cancer.dataset$b <- cancer.dataset$Diagnosis == "B"
cancer.dataset$m = cancer.dataset$Diagnosis == "M"
cancer.dataset$area <- cancer.dataset$Diagnosis == "area"
cancer.dataset$texture = cancer.dataset$Diagnosis == "texture"
cancer.dataset$smoothness = cancer.dataset$Diagnosis == "smoothness"

cancerdata <- data.frame(cancer.dataset$Diagnosis, cancer.dataset$texture, cancer.dataset$smoothness, cancer.dataset$area)
cancerdata

train <- sample(x = nrow(cancerdata), size = nrow(cancerdata)*0.5)
train

cancertrain <- cancer.dataset[train,]
cancervalid <- cancer.dataset[-train,]
print(nrow(cancertrain))
print(nrow(cancervalid))
nn <- neuralnet(B+M~ area+texture+smoothness, data=cancertrain, hidden=3,  
                rep = 2, err.fct = "ce", linear.output = F, lifesign = "minimal", stepmax = 10000000)

这是什么一个例子，是正确定教授看起来像利用的标准虹膜数据集，我不知道如果我做了我的权利的基础上，如何这个人是完成：

iris.dataset$setosa <- iris.dataset$Species=="setosa"
iris.dataset$virginica = iris.dataset$Species == "virginica"
iris.dataset$versicolor = iris.dataset$Species == "versicolor"
train <- sample(x = nrow(iris.dataset), size = nrow(iris)*0.5)
train
iristrain <- iris.dataset[train,]
irisvalid <- iris.dataset[-train,]
print(nrow(iristrain))
print(nrow(irisvalid))
nn <- neuralnet(setosa+versicolor+virginica ~ Sepal.Length + Sepal.Width, data=iristrain, hidden=3,  
                rep = 2, err.fct = "ce", linear.output = F, lifesign = "minimal", stepmax = 10000000)

plot(nn, rep="best")

Question 2

你可以用下面的代码

library(neuralnet)
library(ISLR) 
library(caTools)
library(random)

#setwd("**change to your working directory**")
data <- read.csv("WDBC.csv", header=T)
head(data)

#Select the important variables
cancerdata <- subset(data, select = c(Diagnosis, texture, smoothness, area))
head(cancerdata) 

train <- sample(x = nrow(cancerdata), size = nrow(cancerdata)*0.5)

cancertrain <- cancerdata[train,]
cancervalid <- cancerdata[-train,]
print(nrow(cancertrain))
print(nrow(cancervalid))

nn <- neuralnet(Diagnosis ~ area+texture+smoothness, data=cancertrain, hidden=3,  
                rep = 2, err.fct = "ce", linear.output = F, lifesign = "minimal", stepmax = 10000000)

plot(nn, rep="best")

Bappa Das · Answer 1 · 2021-11-20T05:53:29

你可以用下面的代码

library(neuralnet)
library(ISLR) 
library(caTools)
library(random)

#setwd("**change to your working directory**")
data <- read.csv("WDBC.csv", header=T)
head(data)

#Select the important variables
cancerdata <- subset(data, select = c(Diagnosis, texture, smoothness, area))
head(cancerdata) 

train <- sample(x = nrow(cancerdata), size = nrow(cancerdata)*0.5)

cancertrain <- cancerdata[train,]
cancervalid <- cancerdata[-train,]
print(nrow(cancertrain))
print(nrow(cancervalid))

nn <- neuralnet(Diagnosis ~ area+texture+smoothness, data=cancertrain, hidden=3,  
                rep = 2, err.fct = "ce", linear.output = F, lifesign = "minimal", stepmax = 10000000)

plot(nn, rep="best")

为什么是我的neuralnet功能的工作不在我的计划？

的问题

最好的答案

其他语言

此页面有其他语言版本

受欢迎的此类别

流行的问题，在这个类别