## What is CP in rpart?

cp: Complexity Parameter The complexity parameter (cp) in rpart is the minimum improvement in the model needed at each node. It’s based on the cost complexity of the model defined as… For the given tree, add up the misclassification at every terminal node.

**What is positive class in confusion matrix R?**

The confusion matrix is represented by a positive and a negative class. The positive class represents the not-normal class or behavior, so it is usually less represented than the other class. The negative class, on the other hand, represents normality or a normal behavior.

### What is false positive in confusion matrix?

false positives (FP): We predicted yes, but they don’t actually have the disease. (Also known as a “Type I error.”) false negatives (FN): We predicted no, but they actually do have the disease.

**What is detection rate in confusion matrix?**

The confusion matrix allows to express performance metrics such as the detection rate and the false alarm rate. There is a consensus on the definition of the detection rate,also called True Positive Rate (TPR): TPR=TPTP+FN.

## What are true positives and false positives?

A true positive is an outcome where the model correctly predicts the positive class. Similarly, a true negative is an outcome where the model correctly predicts the negative class. A false positive is an outcome where the model incorrectly predicts the positive class.

**What is positive and negative class?**

The classes, A,B,AB, are called positive classes because they contain all positive attributes. The classes α,β,αβ are called negative classes because they have negative attributes. The classes αB and Aβ contain both positive and negative attributes, so they are called mixed or contrary classes.

### What is a true positive rate?

The true positive rate (TPR, also called sensitivity) is calculated as TP/TP+FN. TPR is the probability that an actual positive will test positive. The true negative rate (also called specificity), which is the probability that an actual negative will test negative. It is calculated as TN/TN+FP.

**What is a good true positive rate?**

In a total of 100 subjects known to have a disease, the model correctly predicts 90 subjects having the disease. In this scenario, TP = 90 and FN = 10. Thus, the true positive rate is 90%.

## What is true positive rate and false positive rate?

The hit rate (true positive rate, TPRi) is defined as rater i’s positive response when the correct answer is positive (Xik = 1 and Zk = 1), and the false alarm rate (false positive rate, FPRi) is defined as a positive response when the correct answer is negative (Xik = 1 and Zk = 0).

**What is rpart package in R?**

Rpart is a powerful machine learning library in R that is used for building classification and regression trees. This library implements recursive partitioning and is very easy to use.