AI Platform Notebooks for Lasso Regression and BigQuery Analysis Quiz
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Questions and Answers

What optimization objective maximizes the area under the receiver operating characteristic curve (AUC ROC) value?

  • Minimizing the area under the precision-recall curve
  • Maximizing the area under the receiver operating characteristic curve (correct)
  • Maximizing the area under the precision-recall curve
  • Minimizing the area under the receiver operating characteristic curve
  • In the context of a video sharing website, what is a good measure to determine the success of an ML model predicting popular videos?

  • Predicting 95% of the most popular videos measured by watch time within 30 days of being uploaded (correct)
  • The Pearson correlation coefficient between log-transformed views after 7 and 30 days is equal to 0
  • Predicting videos as popular if the user who uploads them has over 10,000 likes
  • Predicting 97.5% of the most popular clickbait videos measured by number of clicks
  • What should be done to assist gradient optimization when dealing with columns of data having different ranges in a Neural Network project?

  • Use representation transformation (normalization) technique (correct)
  • Utilize Lasso regression analysis for feature selection
  • Improve data cleaning by removing features with missing values
  • Use feature construction to combine the strongest features
  • What method can be used to eliminate features that do not provide a strong signal in a model?

    <p>Lasso regression</p> Signup and view all the answers

    Which Google Cloud tool can be used to determine the impact of excluding individual features on model performance?

    <p>What-If tool</p> Signup and view all the answers

    What function in BigQuery can be used to calculate the Pearson correlation coefficient between features and the target variable?

    <p>CORR()</p> Signup and view all the answers

    In a highly skewed dataset where examples without the company's logo are dominant, which metric would be most suitable to evaluate a classification model?

    <p>Precision-Recall Curve</p> Signup and view all the answers

    Which metric places more emphasis on the ability of the model to capture all positive instances, given a dataset highly imbalanced towards one class?

    <p>F1 Score</p> Signup and view all the answers

    What technique can be used to obtain feature attributions from a model by submitting prediction requests with a specific keyword?

    <p>'explain' keyword in BigQuery</p> Signup and view all the answers

    What approach should you take when building a regression model to minimize effort and training time while maximizing model performance?

    <p>Use AutoML Tables to train the model without early stopping</p> Signup and view all the answers

    In a linear model with over 100 input features, all with values between –1 and 1, what technique is suitable to remove non-informative features?

    <p>Use L1 regularization to reduce the coefficients of uninformative features to 0</p> Signup and view all the answers

    If you suspect that many features are non-informative in your model, what should you do to keep the informative ones while removing the non-informative ones?

    <p>Utilize L1 regularization to eliminate non-informative features</p> Signup and view all the answers

    When building a regression model, what method can you use to identify which features do not degrade the model when removed?

    <p>Use an iterative dropout technique to assess feature importance</p> Signup and view all the answers

    In a high-dimensional dataset with potentially non-informative features, what strategy helps differentiate informative from non-informative features?

    <p>Using recursive feature elimination (RFE) with cross-validation for ranking features</p> Signup and view all the answers

    Which method is most suitable for identifying the least informative features in a regression model and discarding them?

    <p>Employing L2 regularization to penalize unimportant features</p> Signup and view all the answers

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