I am currently solving a problem of classification using xgboost algorithm in R .First I have read the attributes which are needed for creation of a classification model .

```
model <- xgboost(data, label , max.depth , eta , nthread , nround , objective)
```

**data**-Input data

**label**- target variable

**max.depth**-the depth of tree.

**nround**-the number of trees to the model.

**objective** -for regression use ‘reg:linear’ and for binary classification use ‘binary:logistic’.

I am not able to understand what should be the value of eta and nthread and how their value will effect the classification model.