party

partykit ctree formating x and y axis labels

由 二次信任 提交于 2019-12-10 11:41:56
问题 My problem is the newest version of the partykit package seems to remove all x and y axis tics and labels from ctree plots. install.package("partykit") library(partykit) irisct <- ctree(Species ~ .,data = iris) plot(irisct) See ... no x or y labels in the terminal nodes! I want the plots to look like they do in the party package: detach("package:partykit", unload=TRUE) library(party) irisct <- ctree(Species ~ .,data = iris) plot(irisct) From what I have seen online partykit should be able to

Consolidate party rules

由 别等时光非礼了梦想. 提交于 2019-12-10 10:23:21
问题 A simple example >library(partykit) > partykit:::.list.rules.party(ctree(Petal.Length~.,data=iris)) 2 "Petal.Width <= 0.6" 6 "Petal.Width > 0.6 & Sepal.Length <= 6.2 & Petal.Width <= 1.3 & Sepal.Length <= 5.5" 7 "Petal.Width > 0.6 & Sepal.Length <= 6.2 & Petal.Width <= 1.3 & Sepal.Length > 5.5" .... For example, in the second rule, the two occurrences of Sepal.Length can be consolidated into Sepal.Length<=5.5 So, is there a way to consolidate the rules? 回答1: In the plot of the tree below, on

Plot party decision tree

由 自古美人都是妖i 提交于 2019-12-09 13:56:09
问题 I have the following plot as you can see in the picture, Is there any way to see exact number of percentage in the leaf nodes? 回答1: If you want to "see" the percentages, the easiest way is to make a table() of the terminal nodes vs. the response and then look at the conditional proportions. If you want to "see" the proportions in the barplot, then there was no possibility to do this up to now. However, I tweaked the node_barplot() function to accomodate this feature. So if you re-install the

Add horizontal line to terminal barplots in party / partykit trees

由 一世执手 提交于 2019-12-08 04:53:13
问题 I am using the ctree function from partykit . library(rpart) library(partykit) fit <- ctree(Kyphosis ~ Age + Number + Start, data=kyphosis) plot(fit, terminal_panel=node_barplot) I want to add an additional horizonal line to each barplot, indicating the average reponse across the dataset, i.e. at 0.79 here. prop.table(table(kyphosis$Kyphosis)) absent present 0.7901235 0.2098765 Approach : I started to modify the node_barplot function that is passed to the terminal_panel argument. But the

R Extracting inner node information and splits from ctree (partykit)

由 ぃ、小莉子 提交于 2019-12-07 20:43:33
问题 Hi I'm currently trying to extract some of the inner node information stored in the constant partying object in R using ctree in partykit but I'm finding navigating the objects a bit difficult, I'm able to display the information on a plot but I'm not sure how to extract the information - I think it requires nodeapply or another function in the partykit? library(partykit) irisct <- ctree(Species ~ .,data = iris) plot(irisct, inner_panel = node_barplot(irisct)) Plot with inner node details All

Add horizontal line to terminal barplots in party / partykit trees

由 送分小仙女□ 提交于 2019-12-07 02:45:26
I am using the ctree function from partykit . library(rpart) library(partykit) fit <- ctree(Kyphosis ~ Age + Number + Start, data=kyphosis) plot(fit, terminal_panel=node_barplot) I want to add an additional horizonal line to each barplot, indicating the average reponse across the dataset, i.e. at 0.79 here. prop.table(table(kyphosis$Kyphosis)) absent present 0.7901235 0.2098765 Approach : I started to modify the node_barplot function that is passed to the terminal_panel argument. But the source code is very long and comes with almost no comments. So I tried to go step by step, stripping down

Rotate Classification Tree Terminal Barplot axis - R

由 安稳与你 提交于 2019-12-06 13:36:21
I have a classification tree analyzed using ctree() was wondering how can one rotate the terminal nodes so that the axes are vertical? library(party) data(iris) attach(iris) plot(ctree(Species ~ Sepal.Length + Sepel.Width + Petal.Length + Petal.Width, data = iris)) Here is how I would go about it. Not the shortest answer, but I wanted to be as thorough as possible. Since we are plotting your tree, it's probably a good idea to look at the documentation for the appropriate plotting function: library(party) data(iris) attach(iris) ctree <- ctree(Species ~ Sepal.Length + Sepal.Width + Petal.Length

Modifying terminal node in ctree(), partykit package

由 岁酱吖の 提交于 2019-12-06 12:34:18
问题 I have a dependent variable to classify by a decision tree. It's composed by three categories of frequences: 738 (19%), 426 (15%) and 1800 (66%). As you imagine the predicted category is always the third one, but the purpose of the tree is descriptive so it does not actually matter. The thing is, when plotting a tree by the ctree() function (package partykit ) the terminal nodes display histograms showing the probability of occurrence of the three classes. I need to modify this output: I

R Extracting inner node information and splits from ctree (partykit)

由 与世无争的帅哥 提交于 2019-12-06 06:52:00
Hi I'm currently trying to extract some of the inner node information stored in the constant partying object in R using ctree in partykit but I'm finding navigating the objects a bit difficult, I'm able to display the information on a plot but I'm not sure how to extract the information - I think it requires nodeapply or another function in the partykit? library(partykit) irisct <- ctree(Species ~ .,data = iris) plot(irisct, inner_panel = node_barplot(irisct)) Plot with inner node details All the information is accessible by the functions to plot, but I'm after a text output similar to:

Consolidate party rules

由 拟墨画扇 提交于 2019-12-05 20:07:58
A simple example >library(partykit) > partykit:::.list.rules.party(ctree(Petal.Length~.,data=iris)) 2 "Petal.Width <= 0.6" 6 "Petal.Width > 0.6 & Sepal.Length <= 6.2 & Petal.Width <= 1.3 & Sepal.Length <= 5.5" 7 "Petal.Width > 0.6 & Sepal.Length <= 6.2 & Petal.Width <= 1.3 & Sepal.Length > 5.5" .... For example, in the second rule, the two occurrences of Sepal.Length can be consolidated into Sepal.Length<=5.5 So, is there a way to consolidate the rules? In the plot of the tree below, on the way to node 6 (the node whose rules you reference in your question) we first keep only points with Petal
订阅 party