Podcast
Questions and Answers
What term describes the situation when a model performs well on training data but poorly on new test data?
What term describes the situation when a model performs well on training data but poorly on new test data?
- Overfitting (correct)
- Generalizing
- Converging
- Underfitting
In machine learning, what is the term used to describe the process of estimating the output for new data points based on known training data?
In machine learning, what is the term used to describe the process of estimating the output for new data points based on known training data?
- Interpolating
- Spanning
- Predicting (correct)
- Generalizing
Which machine learning method will be introduced first in the text?
Which machine learning method will be introduced first in the text?
- Support Vector Machines (SVM)
- K-Nearest Neighbors (k-NN) (correct)
- Decision Trees
- Linear Regression
What does the k-Nearest Neighbors (k-NN) method rely on for making predictions?
What does the k-Nearest Neighbors (k-NN) method rely on for making predictions?
When a model is described as 'generalizing,' what characteristic does it possess?
When a model is described as 'generalizing,' what characteristic does it possess?
What issue arises when a model is unable to generalize beyond the training data?
What issue arises when a model is unable to generalize beyond the training data?
What outcome results from a model that is overfitting to the training data?
What outcome results from a model that is overfitting to the training data?
What is the primary challenge with a model that overfits the training data?
What is the primary challenge with a model that overfits the training data?
What does it mean when a model 'overfits' to the training data?
What does it mean when a model 'overfits' to the training data?
'Overfitting' in machine learning is often associated with which of the following?
'Overfitting' in machine learning is often associated with which of the following?
