Neural Network in R

 library(neuralnet)# creating training data setTAWKIR=c(20,10,30,20,80,30)AHMED=c(90,20,40,50,50,80)Placed=c(1,0,0,0,1,1)# Here, you will combine multiple columns or features into a single set of datadf=data.frame(TAWKIR,AHMED,Placed)# load libraryrequire(neuralnet)# fit neural networknn=neuralnet(Placed~TAWKIR+AHMED,data=df,...

Bar plot

 plot(rf,$a xlib= " ", ylib=" ", main = "Error in different tree...

Random Forest plot

 library(randomForest)# Load the dataset and exploredata1 <- read.csv(file.choose(), header = TRUE)head(data1)str(data1)summary(data1)# Split into Train and Validation sets# Training Set : Validation Set = 70 : 30 (random)set.seed(1000)train <- sample(nrow(data1), 0.7*nrow(data1), replace...

SHAP plot

 #Part 1: library inputsuppressPackageStartupMessages({  library(SHAPforxgboost)  library(xgboost)  library(data.table)  library(ggplot2)})#part 2:#file load and shap value calculationa <- read.csv(file.choose())X1 = as.matrix(a[,-1])mod1 = xgboost::xgboost(  data =...

Text plot

 ## A blank plot to set up a coordinate system## Final result will be Figure 3-42> plot(0:10, 0:10, type = "n")## Some regular text as a baselinetext(2,10, "Regular text", pos = 4)## Set text larger and use serif familypar(list(cex = 2, family = "serif"))## Add some texttext(2,8, "Serif Family",...

Bi Plot for PCA

 ## Use datasets:USArrestsdata(USArrests) # Get datafilenames(USArrests) # View variable names## Scaled PCA using entire data.framepca1 = prcomp(USArrests, scale = TRUE)## Both following commands produce same PCA as previouspca2 = prcomp(~., data = USArrests, scale = TRUE)pca3 = prcomp(~ Murder...

Scree plot from PCA

 ## Use datasets:USArrestsdata(USArrests) # Get datafilenames(USArrests) # View variable names## Scaled PCA using entire data.framepca1 = prcomp(USArrests, scale = TRUE)## Both following commands produce same PCA as previouspca2 = prcomp(~., data = USArrests, scale = TRUE)pca3 = prcomp(~ Murder...

Pic chart

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Dot chart

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Bar chart

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Line plot

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Scatter plot

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