Intro to ML: The ML Revision Quiz

Intro to ML: The ML Revision Quiz

Assessment

Assessment

Created by

Josiah Wang

Computers

University

20 plays

Hard

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11 questions

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1.

Multiple Choice

1 min

1 pt

If we predict every observation to be True, what will our model precision be?

100%

0%

The proportion of True values in the dataset

Not enough information

Answer explanation

Media Image

Think of all the False Positives

2.

Multiple Select

1 min

1 pt

James, Amelia, and George are participating in a machine learning competition. They have to choose an algorithm for their project. Select which of the following algorithms they should consider if they want to use eager learners:

K-nearest neighbours

Decision trees

Neural networks

Linear regression

Answer explanation

Recall that K-nn is a lazy learner. At training time the algorithm simply stores the training data - i.e. no calculations/training occurs. It is not until inference time when the algorithm checks the K nearest points to the unseen datapoint in question. All calculations occur at inference time, hence being called lazy rather than eager.

3.

Multiple Select

1 min

1 pt

Which of the following statements are True:

Performance on the validation set can be used to see if a model is overfitting to the training data

We cannot tell from the training performance alone if a model is overfitting or not

Underfitting implies better generalisation to other datasets

Answer explanation

Underfitting is when the model lacks the capacity to fit the underlying pattern/trend of the data. A model that underfits a training set will perform no better on unseen data.

4.

Multiple Select

1 min

1 pt

Scarlett is working on a machine learning project and she is worried about underfitting. Which of the following actions may cause underfitting in her model?

Reducing the max. depth of a decision tree

Increasing the value of K in K-nn

Adding more layers to a neural network

Increasing the size of the training data

Increasing the value of K in K-means

Answer explanation

Underfitting is caused when the model lacks the capacity to fit the underlying trend/pattern of the data.

5.

Multiple Choice

1 min

1 pt

True or False:

If we use grid-search for testing different hyper-parameter values, we can use each of these results for finding the confidence interval of the model error.

True

False

Answer explanation

Confidence Intervals should be reported for the final model architecture. They are a prediction on how the final model will perform on unseen data. If this is calculated with a range of different models, this will clearly be an inaccurate prediction.

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