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Jiancong Shen Assignment 5 #98

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Jiancong Shen Assignment 5 #98

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43d1d9b
Jiancong Shen Assignment 5
Nov 15, 2019
409f4f0
yeah
Nov 20, 2019
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4 changes: 2 additions & 2 deletions Assignment 5.Rmd
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Expand Up @@ -61,7 +61,7 @@ plot(score_ctree)
```

Please interpret the tree, which two behaviors do you think the teacher should most closely pay attemtion to?
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Try to answer this question.


The teacher should pat attention to prior_prob_count and hints, since they are two deteermining factors in the graph.
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Try to elaborate on it based on the information from the decision tree.

#Test Tree
Upload the data "intelligent_tutor_new.csv". This is a data set of a differnt sample of students doing the same problems in the same system. We can use the tree we built for the previous data set to try to predict the "advice" we should give the teacher about these new students.

Expand All @@ -81,7 +81,7 @@ Compare the predicted advice with the actual advice that these students recieved
D2$advice <- ifelse(D2$score>=0.8,1,ifelse(D2$score<=0.5,3,2))
accuracy<-nrow(filter(D2,prediction==1))/nrow(D2)

#The predicted score is 65% accurate.
#The predicted score is 65% accurate. The model is too generalized we can have more variables add to the graph. The error rate is 35%.
```
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Overall, great job on the coding part of this assignment but you may want to work on the analysis.


### To Submit Your Assignment
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