Why boosting does not Improve the performance of the model

r
classification
boosting

#1

I am currently trying to solve a problem on classification problem using boosting in R but when I have built the model using boosting my performance does not increase rather it decrease when I am using only rpart

‘data.frame’: 891 obs. of 12 variables:
PassengerId: int 1 2 3 4 5 6 7 8 9 10 ... Survived : int 0 1 1 1 0 0 0 0 1 1 …
Pclass : int 3 1 3 1 3 3 1 3 3 2 ... Name : Factor w/ 891 levels “Abbing, Mr. Anthony”,…: 109 191 358 277 16 559 520 629 417 581 …
Sex : Factor w/ 2 levels "female","male": 2 1 1 1 2 2 2 2 1 1 ... Age : num 22 38 26 35 35 NA 54 2 27 14 …
SibSp : int 1 1 0 1 0 0 0 3 0 1 ... Parch : int 0 0 0 0 0 0 0 1 2 0 …
Ticket : Factor w/ 681 levels "110152","110413",..: 524 597 670 50 473 276 86 396 345 133 ... Fare : num 7.25 71.28 7.92 53.1 8.05 …
Cabin : Factor w/ 148 levels "","A10","A14",..: 1 83 1 57 1 1 131 1 1 1 ... Embarked : Factor w/ 4 levels “”,“C”,“Q”,“S”: 4 2 4 4 4 3 4 4 4 2 …

titanic.adaboost <- boosting(Survived ~ ., data=new_train, mfinal=1000)
I have created the model using mfinal=1000 but my classification not better than simple rpart.