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module-4-quiz.txt
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1. Separate the data into distinct groups by similarity
2. Trees are easy to interpret and visualize, Trees often require less preprocessing of data
3. To improve generalization by reducing correlation among the trees and making the model more robust to bias.
4. Support Vector Machines, Naive Bayes - X
5. For predicting future sales of a clothing line, Linear regression would be a better choice than a decision tree regressor., For a fitted model that doesn’t take up a lot of memory, KNN would be a better choice than logistic regression., For a model that won’t overfit a training set, Naive Bayes would be a better choice than a decision tree. - X
6. Neural Network, KNN (k=1), Decision Tree
7. 0.5 - X
8. collection_status - Flag for payments in collections, compliance_detail - More information on why each ticket was marked compliant or non-compliant
9. If time is a factor, remove any data related to the event of interest that doesn’t take place prior to the event., Remove variables that a model in production wouldn’t have access to, Sanity check the model with an unseen validation set
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