I am currently trying to implement the boosting model in R and while searching about it I have found the formula of bagging model.

```
boosting(formula, data, boos , mfinal , coeflearn , control)
```

There are six attributes in the model

Formula

data

boos

mfinal

coeflearn

control

**formula**

as in the lm function.

**data**

a data frame, help to interpret the variables named in the formula

**mfinal**

an integer, the number of iterations for which boosting is run or the number of trees to use. Defaults to mfinal=100 iterations.

**control**

controls details of the rpart algorithm.

I want to know the values of boss and coeflearn argument and how these values affect the performance of boosting model.