the nuts and bolts of machine learning coursera week 2 quiz answers
Test your knowledge: PACE in machine learning: The plan and analyze stages
1. Fill in the blank: Feature engineering enables data professionals to take _____ and extract features from it.
- delimited text
- a dynamic dashboard
- a code chunk
- raw data
2. What term describes the process of modifying existing features in a way that improves accuracy when training a model?
- Feature selection
- Feature extraction
- Feature improvement
- Feature transformation
3. A class imbalance occurs when a dataset has a predictor variable that contains an equal number of instances of all possible outcomes.
- True
- False
Test your knowledge: PACE in machine learning: The construct and execute stages
4. Fill in the blank: Posterior probability is the probability of an event occurring after considering _____ information.
- historical
- undefined
- conditional
- new
5. A data professional would use the function MinMaxScaler to normalize the columns in a model so that each value falls between zero and one.
- True
- False
6. A data professional has built a model, and now they are adjusting how features are engineered in order to improve performance. Which PACE stage does this scenario describe?
- Plan
- Execute
- Analyze
- Construct
Weekly challenge 2
7. Which of the following statements accurately describe the general categories of feature engineering? Select all that apply.
- Feature transformation involves modifying existing features in a way that improves accuracy when training a model.
- Feature extraction involves choosing the features in the data that contribute the most to predicting the response variable.
- The three general categories of feature engineering are selection, extraction, and transformation.
- Feature selection involves taking multiple features to create a new one that will improve the accuracy of the algorithm.
8. Which of the following datasets contains a class imbalance that will likely create a problem during analysis?
- A dataset whose majority class comprises 70% of the data and minority class comprises 30% of the data
- A dataset whose majority class comprises 90% of the data and minority class comprises 10% of the data
- A dataset whose classes are split equally, each comprising 50% of the data
- A dataset whose majority class comprises 60% of the data and minority class comprises 40% of the data
Shuffle Q/A 1
9. Fill in the blank: Customer churn is a business term that describes how many customers stop _____ and at what rate this occurs.
- doing business with a company
- writing positive reviews about a company
- returning items to a company
- contacting a company’s customer relations department
10. Naive Bayes’s theorem enables data professionals to calculate posterior probability for a data project. What does posterior probability describe?
- The likelihood of an event occurring after taking into consideration only the most suitable observations and information
- The likelihood of an event occurring after taking into consideration all new, relevant observations and information
- The likelihood of an event occurring based upon the observations and information that were available at the start of the data project
- The likelihood of an event occurring based upon only observations and information that align with current hypotheses
