Alteryx Advanced - Exercise 5

The video tutorial guides viewers through creating a regression model to predict house prices using an assisted modeling tool. It covers importing a CSV dataset, preparing data types, creating estimation and validation samples, and setting up the machine learning pipeline. The tutorial emphasizes selecting the target variable, choosing the right features, and comparing model results to identify the best model. Finally, it demonstrates validating the model and analyzing prediction accuracy using Random Forest.

Explain the role of the assisted modeling tool in the workflow.

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What criteria should be used to select the best model from the results?

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What does the predicted price value indicate in relation to the original price?

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