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finish! #91

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We can see that based on the model we've generated from the old data, the degree of accuracy predicting the new data is only 58%. I don't think this is a very accurate prediction.

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Try to be more specific, as in, state whether the model is generalizable or does it overfit.


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## Part III
Compare the predicted advice with the actual advice that these students recieved. What is the difference between the observed and predicted results?

```{r}
# all the students in the new dataset achieved a score of 1.0, therefore, the accuracy of our model's prediction would be:
mean(ifelse(D2$prediction == "no action", 1, 0))

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Another way to calculate the accuracy of the model's prediction is to create a table or a confusion matrix.

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Please interpret the tree, which two behaviors do you think the teacher should most closely pay attemtion to?

Interpret from this plot, the students who are asking for hints for less than 12 times and have less than 63% questions answered correctly before this session are very likely to need intervention (node7). Other than that, students who do not ask for any hints, while have answered less than 85 questions correctly are also quite likely need interventions(node 3). Therefore, I think "students that ask for less than 12 hints" and "have answered less than 85 questions correctly" are the two most important behaviors that teachers should pay close attention to.

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Great work!


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We can see that based on the model we've generated from the old data, the degree of accuracy predicting the new data is only 58%. I don't think this is a very accurate prediction.

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Overall, great job. Keep up the good work!

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