如何在 RPART 中获取决策树的一个终端节点中的数据
How can I get the data in one terminal node of a decision tree in RPART
假设我有一个来自rpart的决策树，如何在不写所有条件的情况下获取一个节点中的所有数据点？
例如，如何在节点 3 中获取 17 个数据点，而无需在所有拆分上写入 if else？
library(rpart)
library(partykit)
fit=rpart(factor(am)~.,mtcars,control=rpart.control(minsplit = 2),cp=0)
plot(as.party(fit))
试试这个：
fit$where[fit$where==3] # for Node 3
# Hornet 4 Drive Hornet Sportabout Valiant Duster 360 Merc 240D Merc 280 Merc 280C
# 3 3 3 3 3 3 3
# Merc 450SE Merc 450SL Merc 450SLC Cadillac Fleetwood Lincoln Continental Chrysler Imperial Dodge Challenger
# 3 3 3 3 3 3 3
# AMC Javelin Camaro Z28 Pontiac Firebird
3 3 3
length(fit$where[fit$where==3])
#[1] 17
mtcars[rownames(mtcars) %in% names(fit$where[fit$where==3]),]
# mpg cyl disp hp drat wt qsec vs am gear carb x
#Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 4
#Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 5
#Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 6
#Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 7
#Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 8
#Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 10
#Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 11
#Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 12
#Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 13
#Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 14
#Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 15
#Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 16
#Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 17
#Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 22
#AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 23
#Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 24
#Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 25
假设我有一个来自rpart的决策树，如何在不写所有条件的情况下获取一个节点中的所有数据点？
例如，如何在节点 3 中获取 17 个数据点，而无需在所有拆分上写入 if else？
library(rpart)
library(partykit)
fit=rpart(factor(am)~.,mtcars,control=rpart.control(minsplit = 2),cp=0)
plot(as.party(fit))
试试这个：
fit$where[fit$where==3] # for Node 3
# Hornet 4 Drive Hornet Sportabout Valiant Duster 360 Merc 240D Merc 280 Merc 280C
# 3 3 3 3 3 3 3
# Merc 450SE Merc 450SL Merc 450SLC Cadillac Fleetwood Lincoln Continental Chrysler Imperial Dodge Challenger
# 3 3 3 3 3 3 3
# AMC Javelin Camaro Z28 Pontiac Firebird
3 3 3
length(fit$where[fit$where==3])
#[1] 17
mtcars[rownames(mtcars) %in% names(fit$where[fit$where==3]),]
# mpg cyl disp hp drat wt qsec vs am gear carb x
#Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 4
#Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 5
#Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 6
#Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 7
#Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 8
#Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 10
#Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 11
#Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 12
#Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 13
#Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 14
#Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 15
#Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 16
#Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 17
#Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 22
#AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 23
#Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 24
#Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 25