IBM Data Science Test 2025 – 400 Free Practice Questions to Pass the Exam

Image Description

Question: 1 / 400

What does "data leakage" refer to in machine learning?

The intentional sharing of training data

A type of data visualization error

The inclusion of information giving unfair advantage

Data leakage occurs when information is included in the training dataset that should not be available during the training process, leading to overly optimistic performance metrics for the model. This information could be future data or data derived from the outcome variable that the model is trying to predict, which provides an unfair advantage by allowing the model to learn patterns from data that wouldn't be available at prediction time.

This situation can lead to models that perform exceptionally well on training and validation sets but fail to generalize to new, unseen data, as they have essentially 'cheated' by having access to information that they should not have. Recognizing and preventing data leakage is crucial for building robust and reliable machine learning systems.

Get further explanation with Examzify DeepDiveBeta

The loss of data during model training

Next Question

Report this question

Download IBM Data Science Practice Test PDF Study Guide
Subscribe

Get the latest from Examzify

You can unsubscribe at any time. Read our privacy policy