Quiz Time: How Much Do You Know?
Quiz Time: How Much Do You Know? Data Science Project
Classification in Depth with Scikit-Learn

Quiz Time: How Much Do You Know?

In this project you will be asked to complete some minor challenges to test your knowledge of Classification.
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Quiz Time: How Much Do You Know?Quiz Time: How Much Do You Know?
Project Created by

Verónica Barraza

Project Activities

All our Data Science projects include bite-sized activities to test your knowledge and practice in an environment with constant feedback.

All our activities include solutions with explanations on how they work and why we chose them.

multiplechoice

Which of the following statement is the correct one?

multiplechoice

Select which of the following scenarios are classification problems.

multiplechoice

At what point in the pipeline process are the parameters adjusted?

multiplechoice

What are some common evaluation metrics used for classification tasks?

multiplechoice

Decision trees can be used for both classification and regression tasks.

multiplechoice

In a learning problem with 2D features, what is the relationship between decision tree and 1-nearest neighbor decision boundaries?

multiplechoice

What does 'naive' mean in Naive Bayes?

multiplechoice

How does ensemble learning improve model performance?

multiplechoice

Given a confusion matrix for a binary classification problem, how would you compute the precision score?

input

We build a model and test it on a set of 100 customer records, and the resulting confusion matrix is as follows:

Predicted Negative Predicted Positive
Actual Negative 70 10
Actual Positive 5 15

Compute the precision score to one decimal place

multiplechoice

We build a model and test it on a set of 100 customer records, and the resulting confusion matrix is as follows:

Predicted Negative Predicted Positive
Actual Negative 80 5
Actual Positive 5 20

Compute the recall score to one decimal place

multiplechoice

As a reviewer for an international conference, you have been given papers with different experimental setups to review. Based on the content of each paper, would you recommend accepting or rejecting them?

In comparison to your algorithm, mine appears to be more effective. I suggest observing the training error rates for confirmation.

multiplechoice

For k cross-validation, larger k value implies more bias.

multiplechoice

Let´s suppose three classifications model are built to discriminate apples from bananas. The following table shows the results obtained according to these algorithms:

model Model 1 Model 2 Model 3
Accuracy (training) 0.99 0.93 0.99
Accuracy (testing) 0.90 0.75 0.10
Quiz Time: How Much Do You Know?Quiz Time: How Much Do You Know?
Project Created by

Verónica Barraza

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Classification in Depth with Scikit-Learn

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