神经网络

作者

[编辑] 郑虎;

[审核] .

注记

Hiplot 网站

本页面为 Hiplot Neural Network 插件的源码版本教程，您也可以使用 Hiplot 网站实现无代码绘图，更多信息请查看以下链接:

https://hiplot.cn/basic/neural-network?lang=zh_cn

环境配置

系统: Cross-platform (Linux/MacOS/Windows)
编程语言: R
依赖包: data.table; jsonlite; NeuralNetTools; nnet

# 安装包
if (!requireNamespace("data.table", quietly = TRUE)) {
  install.packages("data.table")
}
if (!requireNamespace("jsonlite", quietly = TRUE)) {
  install.packages("jsonlite")
}
if (!requireNamespace("NeuralNetTools", quietly = TRUE)) {
  install.packages("NeuralNetTools")
}
if (!requireNamespace("nnet", quietly = TRUE)) {
  install.packages("nnet")
}

# 加载包
library(data.table)
library(jsonlite)
library(NeuralNetTools)
library(nnet)

数据准备

# 加载数据
data <- data.table::fread(jsonlite::read_json("https://hiplot.cn/ui/basic/neural-network/data.json")$exampleData$textarea[[1]])
data <- as.data.frame(data)

# 查看数据
head(data)

         Y1        Y2          X1         X2         X3
1 0.7646258 0.5494452 -0.89691455 -1.8923489  0.6408445
2 0.2383994 0.4605024  0.18484918  1.2928042 -1.6013778
3 0.3800247 0.2527468  1.58784533 -0.6182543 -0.7778154
4 0.3545279 0.6319730 -1.13037567  1.0409383 -1.6473925
5 0.3667356 0.4684437 -0.08025176  1.1758795  0.1542662
6 0.5509560 0.4439474  0.13242028 -1.5018321 -1.1756313

可视化

# 神经网络
mod <- nnet(Y1 ~ X1 + X2 + X3, data = neuraldat, size = 10,
            maxint = 100, decay = 0)

# weights:  51
initial  value 78.500691 
iter  10 value 0.337066
iter  20 value 0.192314
iter  30 value 0.152626
iter  40 value 0.141174
iter  50 value 0.135013
iter  60 value 0.078199
iter  70 value 0.043228
iter  80 value 0.031472
iter  90 value 0.023796
iter 100 value 0.019665
final  value 0.019665 
stopped after 100 iterations

# plot
par(mar = numeric(4))
plotnet(mod)