What does autogluon suggest in case it inferred wrong metric

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Reference no: EM133770159

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A. What is the shape of the training dataset?

B. What type of ML problem (such as classification or regression) does AutoGluon infer? (Hint: Remember, you didn't mention the problem type. You only provided the label column.)

C. What does AutoGluon suggest in case it inferred the wrong problem type?

D. What kind of data preprocessing and feature engineering did AutoGluon perform?

E. What are the basic statistics about the label in the print statements from AutoGluon?

F. How many extra features were generated in addition to the originals in the dataset? What was the runtime for that?

G. Which evaluation metric was used?

H. What does AutoGluon suggest in case it inferred the wrong metric?

I. What is the ratio between the training and validation dataset? (Hint: Look for val or validation.)

J. Where did AutoGluon save the predictor?

K. Which folder were the models saved in?

L. What file format are the models in? (Note: Look at the file name suffix. You don't need to open the file.)

Reference no: EM133770159

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