Practice More Quizzes:
Q:
You use an Azure Machine Learning designer pipeline to train and test a binary classification model. You review the model’s performance metrics in an Evaluate Model module, and note that it has an AUC score of 0.6. What can you conclude about the model?
Q:
Which metric presents the ratio of correct predictions (true positives + true negatives) to the total number of predictions?
Q:
Which metric presents the fraction of positives cases correctly identified?
Q:
Which of the following scenarios can be resolved by applying classification models?
Q:
Which of the following are models that help predict between two or several categories? Select all that apply.
Q:
True or False? Classification is an example of a supervised machine learning technique in which you train a model using data that includes both the features and known values for the label, so that the model learns to fit the feature combinations to the label.
Q:
You are using Azure Machine Learning designer to create a training pipeline for a binary classification model.At some point, you want to separate the data into training and testing sets. Which model should you add to the pipeline?
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