What is the primary purpose of evaluation metrics in machine learning?
Practice Questions
1 question
Q1
What is the primary purpose of evaluation metrics in machine learning?
To improve model training speed
To assess model performance
To increase data size
To reduce overfitting
Evaluation metrics are used to assess how well a machine learning model performs on a given task.
Questions & Step-by-step Solutions
1 item
Q
Q: What is the primary purpose of evaluation metrics in machine learning?
Solution: Evaluation metrics are used to assess how well a machine learning model performs on a given task.
Steps: 5
Step 1: Understand that machine learning models are created to make predictions or decisions based on data.
Step 2: Realize that we need a way to check if these predictions or decisions are correct or useful.
Step 3: Learn that evaluation metrics are tools or measures that help us see how well the model is doing.
Step 4: Know that these metrics can show us different aspects of the model's performance, like accuracy, precision, or recall.
Step 5: Conclude that the primary purpose of evaluation metrics is to provide a clear way to assess and compare the performance of machine learning models.
