Neural Network

Authors

[Editor] Hu Zheng;

[Contributors]

Note

Hiplot website

This page is the tutorial for source code version of the Hiplot Neural Network plugin. You can also use the Hiplot website to achieve no code ploting. For more information please see the following link:

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

Setup

System Requirements: Cross-platform (Linux/MacOS/Windows)
Programming language: R
Dependent packages: NeuralNetTools; nnet

# Install packages
if (!requireNamespace("NeuralNetTools", quietly = TRUE)) {
  install.packages("NeuralNetTools")
}
if (!requireNamespace("nnet", quietly = TRUE)) {
  install.packages("nnet")
}

# Load packages
library(NeuralNetTools)
library(nnet)

Data Preparation

# Load data
data <- read.delim("files/Hiplot/129-neural-network-data.txt", header = T)

# View data
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

Visualization

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

# weights:  51
initial  value 106.598439 
iter  10 value 0.420388
iter  20 value 0.197764
iter  30 value 0.121837
iter  40 value 0.068623
iter  50 value 0.044670
iter  60 value 0.032498
iter  70 value 0.023569
iter  80 value 0.017268
iter  90 value 0.012970
iter 100 value 0.009849
final  value 0.009849 
stopped after 100 iterations

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