Review the airline sentiment data set included with this exam. This data set is saved in...

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Review the airline sentiment data set included with this exam. This data set is saved in an Excel spreadsheet and contains 4 columns (ID, sentiment, airline, and text). Sentiment can be either positive, negative, or neutral. Answer the following questions. You may need to do some analysis with Python on the data set to answer some of these questions. Some of the sections below are tasks instead of questions. If the question is labelled as a task, perform the task. There will not be a question to answer for these tasks. Use the tools available for these tasks. For example, sometimes it is easier to accomplish something in Excel rather than writing code to do the task. 4. (10 points) Report the confusion matrix for the model predictions on the training data. What is the overall accuracy of the model? Are there differences between the recall and precision values for positive versus negative? (Ctrl) Review the airline sentiment data set included with this exam. This data set is saved in an Excel spreadsheet and contains 4 columns (ID, sentiment, airline, and text). Sentiment can be either positive, negative, or neutral. Answer the following questions. You may need to do some analysis with Python on the data set to answer some of these questions. Some of the sections below are tasks instead of questions. If the question is labelled as a task, perform the task. There will not be a question to answer for these tasks. Use the tools available for these tasks. For example, sometimes it is easier to accomplish something in Excel rather than writing code to do the task. 4. (10 points) Report the confusion matrix for the model predictions on the training data. What is the overall accuracy of the model? Are there differences between the recall and precision values for positive versus negative? (Ctrl)

Answer rating: 100% (QA)

The confusion matrix for the model predictions on ... View the full answer