Question

The goal in predictive analysis is to use training data to learn a model that can make predictions on new data. Answer the following questions. a. Suppose we increased the size of the training set. Would this likely improve or deteriorate the performance of the model on new data? Why? Increasing the size of the training set is likely to improve the model's performance on new data. Increasing the size of the training set tends to add more variability to the data. More variability tends to make it easier to detect which features are truly correlated with the target class and which features are not. b) Suppose we reduced the feature representation to include only the features with the highest mutual information with the target concept. Would this likely improve or deteriorate the performance of the model on new data? Why?

          The goal in predictive analysis is to use training data to learn a model that can make predictions on new data. Answer the following questions.

a. Suppose we increased the size of the training set. Would this likely improve or deteriorate the performance of the model on new data? Why?
Increasing the size of the training set is likely to improve the model's performance on new data. Increasing the size of the training set tends to add more variability to the data. More variability tends to make it easier to detect which features are truly correlated with the target class and which features are not.

b) Suppose we reduced the feature representation to include only the features with the highest mutual information with the target concept. Would this likely improve or deteriorate the performance of the model on new data? Why?

Added by Lori B.

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