Help Required for R Markdown function.

The "confusionMatrix" function appears to be from the 'caret' package.
Have you loaded 'caret' with the library(caret) command?

On Sat, 27 Feb 2021 at 14:20, Kishor raut <rautkishor01 at gmail.com> wrote:

Respected Sir,

I Mr Kishor Tried to get help online but wont found the solution so
writting an email.

Step1: While writting in rmarkdown all codes get executted very well till
the fuction
Confusionmatrix were written on it.

Step2: As confusionmatrix command inserted following error is on screen
board


processing file: RMarkdown.Rmd
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Quitting from lines 98-104 (RMarkdown.Rmd)
Error in confusionMatrix(p1, train$CTestresult) :
  could not find function "confusionMatrix"
Calls: <Anonymous> ... handle -> withCallingHandlers -> withVisible ->
eval
-> eval

Execution halted

Step4: As codes were written these


Using function ?sample? the data takes into sample of the specified size
from the stored data
```{r}
set.seed(1234)
ind<-sample(2,nrow(FEVER1),replace=TRUE, pro = c(0.7,0.3))
train<-FEVER1[ind==1,]
test<-FEVER1[ind==2,]
```

Application of Random Forest

```{r}
library(randomForest)
set.seed(123)
rfmodel<-randomForest(CTestresult~.,data = train,prox=TRUE)    # Random
Forest Model
plot(rfmodel,main="RandomForest Model")
print(rfmodel,train)                    # Printing Outcome of 'model for
Training Data

```

Prediction using Randome Forest Model
```{r}
# Prediction  of RandomForest Intial Model for Test and Train Data

ptrain1<-predict(rfmodel,train)              # Predicting model Prediction
On Training Data
  # First Six Outcomes with prediction
head(ptrain1)                              # Printing First Six Prediction
using Random Forest Model
head(train$CTestresult)                       # Printing First Six (6)
Actual outcomes

```


Tuning Model:
Tuning of Machine learning model is important step for building good model
for best outcome of research.

```{r}
# Tunning RandomForest  Model using Algorithm

t<-tuneRF(train[,-11],train$CTestresult, mtryStart = 2,ntreeTry = 100,
stepFactor =2,improve = 0.051,trace = TRUE, plot = TRUE, doBest=TRUE)


```

Building New Model:

New model was build on the basis of tunned model parameters and controls.

```{r}
# New Model After Tuning Random Forest Model

rf1<-randomForest(CTestresult~.,data = train,ntree = 100, mtry = 8,
importance = TRUE,proximity = TRUE)

print(rf1)
```

Prediction and Confusion MAtrix:

outcome of model will mesuare with the help of predictive outcomes with
the
help of confusion matrix.

```{r}
# Prediction using Random Forest and Confusion Matrix for Train Data
p1<-predict(rf1,train)
cmatrix<-confusionMatrix(p1,train$CTestresult)
cmatrix


```


I will great thank full if you will help me for to remove the error.




--
*Kind Regards*

Kishor Raut
*Cell No.-07387706552*

        [[alternative HTML version deleted]]

--
John Kane
Kingston ON Canada