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Recursive Partitioning and Regression Trees

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[How to interpret xerror of rpart (method="class") when losses are assigned](https://stackoverflow.com/questions/37736868/how-to-interpret-xerror-of-rpart-method-class-when-losses-are-assigned) ![image](https://github.com/bethatkinson/rpart/assets/5112397/3e6bb95d-43ca-4939-ba7b-d7a1f16a766d) Strangely initial xerror is extremely small and it is 0.1000 (I see this is 1/loss of class 0),...

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why it is the predicted probability of survival, not die? "Plotting rpart trees with the rpart.plot package" p3 ![PixPin_2024-03-01_20-57-15](https://github.com/bethatkinson/rpart/assets/5112397/1d7a97bb-5410-4f47-ba73-b8fb101c8331)

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https://cran.r-project.org/web/packages/rpart/vignettes/longintro.pdf ![image](https://github.com/bethatkinson/rpart/assets/5112397/206d83d4-e14e-4075-a6be-0baaacf6a70f) What's the meaning of “54”? What's the meaning of “0.6301370 0.3698630”?I guess it is the proportion of each class,but how to determine the corresponding class?

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https://cran.r-project.org/web/packages/rpart/vignettes/longintro.pdf p20 ![image](https://github.com/bethatkinson/rpart/assets/5112397/51b5d937-bfde-43b5-a338-b3286a8e8fef)

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https://cran.r-project.org/web/packages/rpart/vignettes/longintro.pdf p18 ![image](https://github.com/bethatkinson/rpart/assets/5112397/2a26df6a-417c-416e-8e28-448f5dc79083) How to adjust the probabilities for missing data?

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Cost for mis-classification can be used as below: fit

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https://cran.r-project.org/web/packages/rpart/vignettes/longintro.pdf p20: ![image](https://github.com/bethatkinson/rpart/assets/5112397/6c1d0a37-6e75-4730-b1d8-6f61a7691fe6) it is said in p22: ![image](https://github.com/bethatkinson/rpart/assets/5112397/19eb1a60-ef67-4bb5-892b-29c933de9409) I know the default impurity index is gini,but I can not get to know exactly how to calculate it

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pages 11/12 of the rpart vignette covers this topic. https://cran.r-project.org/web/packages/rpart/vignettes/longintro.pdf ________________________________ From: lg21c ***@***.***> Sent: Saturday, February 17, 2024 8:52 AM To: bethatkinson/rpart ***@***.***> Cc: Subscribed ***@***.***> Subject: [EXTERNAL] [bethatkinson/rpart]...

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pages 34 of the rpart vignette covers this topic. https://cran.r-project.org/web/packages/rpart/vignettes/longintro.pdf The last split decreases the cross-validated error. ![image](https://github.com/bethatkinson/rpart/assets/5112397/1f08b30f-242a-4656-a057-8d4a21743d4d)

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