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Adaface Sample Data Science Questions

Here are some sample Data Science questions from our premium questions library (10273 non-googleable questions).

Skills

🧐 Question

Medium

Amazon electronics product feedback
Solve
Amazon's electronics store division has over the last few months focused on getting customer feedback on their products, and marking them as safe/ unsafe. Their data science team has used decision trees for this. 
The training set has these features: product ID, data, summary of feedback, detailed feedback and a binary safe/unsafe tag. During training, the data science team dropped any feedback records with missing features. The test set has a few records with missing "detailed feedback" field. What would you recommend?
A: Remove the test samples with missing detailed feedback text fields
            B: Generate synthetic data to fill in missing fields
            C: Use an algorithm that handles missing data better than decision trees
            D: Fill in the missing detailed feedback text field with the summary of feedback field.

Easy

Fraud detection model
Logistic Regression
Solve
Your friend T-Rex is working on a logistic regression model for a bank, for a fraud detection usecase. The accuracy of the model is 98%. T-Rex's manager's concern is that 85% of fraud cases are not being recognized by the model. Which of the following will surely help the model recognize more than 15% of fraud cases?

Medium

Rox's decision tree classifier
Decision Tree Classifier
Solve
Your data science intern Rox was asked to create a decision tree classifier with 12 input variables. The tree used 7 of the 12 variables, and was 5 levels deep. Few nodes of the tree contain 3 data points. The area under the curve (AUC) is 0.86. As Rox's mentor, what is your interpretation?
A. The AUC is high, and the small nodes are all very pure- the model looks accurate.
            B. The tree might be overfitting- try fitting shallower trees and using an ensemble method.
            C. The AUC is high, so overall the model is accurate. It might not be well-calibrated, because the small nodes will give poor estimates of probability.
            D. The tree did not split on all the input variables. We need a larger data set to get a more accurate model.
🧐 Question🔧 Skill

Medium

Amazon electronics product feedback
2 mins
Data Science
Solve

Easy

Fraud detection model
Logistic Regression
2 mins
Data Science
Solve

Medium

Rox's decision tree classifier
Decision Tree Classifier
2 mins
Data Science
Solve
🧐 Question🔧 Skill💪 Difficulty⌛ Time
Amazon electronics product feedback
Data Science
Medium2 mins
Solve
Fraud detection model
Logistic Regression
Data Science
Easy2 mins
Solve
Rox's decision tree classifier
Decision Tree Classifier
Data Science
Medium2 mins
Solve

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Swayam Narain, CTO, Affable

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