r - How to extract top variables from regression tree and use in regression? -


so created regression tree using rpart outputs reg_tree

# show summary statistics of reg_tree summary(reg_tree)  # store top variables new values topvars <- reg_tree$variable.importance  # output of topvars topvars   q_21fb1900   q_2b3296a0          q_0   q_fde6a01e   q_7fa850ed   q_323d6cee   q_c6ab3657   q_eb2ad90d   q_5dcb2b57  5.303283e+15 5.196871e+15 4.002239e+15 4.412505e+14 2.616730e+14 2.162128e+14 2.035465e+14 1.354927e+14 5.095959e+13    q_af2830be   q_caa61b2c   q_a6828865   q_99f5a0bd   q_be83fe28   q_efdc29dd   q_9e86aa7f   q_2ea0e2aa   q_5049294d  2.176437e+13 1.210118e+13 1.126591e+13 8.387189e+12 4.951978e+12 4.115929e+12 3.864235e+12 1.449853e+12 5.436949e+11    q_5ae0f0cd   q_518fba14  5.436949e+11 5.412242e+11

i want extract each of these names xvar1, xvar2 , automatically put them in following model each xvar correspond column heading: lm(y_var ~ xvar1 + xvar2 + xvar3 + ... +,data).

ie

lm(y_var ~ q_21fb1900 + q_2b3296a0 + q_0 + ... +,data)

how do can drop in new data sets , not worry custom changing each xvar in future?

try this:

example: 

reg_tree <- rpart(kyphosis ~ age + number + start, data = kyphosis) topvars <- reg_tree$variable.importance myreg<-lm(as.formula(paste("as.numeric(kyphosis) ~ ",paste(names(topvars), collapse = " + "), sep = "")),data=kyphosis) > summary(myreg)  call: lm(formula = as.formula(paste("as.numeric(kyphosis) ~ ", paste(names(topvars),      collapse = " + "), sep = "")), data = kyphosis)  residuals:      min       1q   median       3q      max  -0.79440 -0.22356 -0.08478  0.10205  0.84768   coefficients:               estimate std. error t value pr(>|t|)     (intercept)  1.2612198  0.1934124   6.521 6.61e-09 *** start       -0.0307392  0.0091166  -3.372  0.00117 **  age          0.0010657  0.0006937   1.536  0.12858     number       0.0525555  0.0274522   1.914  0.05928 .   --- signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1   residual standard error: 0.3599 on 77 degrees of freedom multiple r-squared: 0.2575, adjusted r-squared: 0.2285  f-statistic:   8.9 on 3 , 77 df,  p-value: 3.912e-05

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