## Accuracy
Accuracy measures how close a model's predictions are to the actual values. It is commonly used in classification tasks and is defined as the proportion of correctly predicted labels to the total number of instances.

Formally, accuracy is expressed as:
![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F4420288%2F23a1ac9193ec21d3f9805c9209e0a80e%2Feq.png?generation=1743675585511609&alt=media)

## Submission File
For each ID in the test set, you must predict a probability for the TARGET variable. The file should contain a header and have the following format:

    ID,TARGET
    2,0
    5,0
    6,0
    etc.