swaheera

I tried removing the constraints all together, but now I get a different error: ``` library(mlrMBO) obj.fn = makeMultiObjectiveFunction( name = "My test function", fn = function(x1, x2, x3, x4)...

Thank you for the correction - I found another typo : "ctrl" vs "control". I fixed both of these errors but now I have a new error.

``` library(mlrMBO) obj.fn = makeMultiObjectiveFunction( name = "My test function", fn = function(x1, x2, x3, x4) { var_1

Hello Dr. Richter, Thank you for your reply. I removed the "best.predicted" statement, but the code is still not working: ``` library(mlrMBO) obj.fn = makeMultiObjectiveFunction( name = "My test function",...

Hello Dr. Richter,, Can you please take a look at this if you have some time? Thanks

I repaced [x1], x[2], x[3], x[4] with x1, x2, x3, x4: ``` library(mlrMBO) library(dplyr) library(ParamHelpers) a1 = rnorm(1000,100,10) b1 = rnorm(1000,100,9) c1 = sample.int(1000, 1000, replace = TRUE) train_data =...

@AnotherSamWilson : can you please explain how would someone add constraints to the acquisition function? thanks

> @swaheera have you taken a look at the [tidyrules](https://CRAN.R-project.org/package=tidyrules) package? The vignette contains an example using **rpart** and seems to give exactly what you are looking for. I dont...

@bethatkinson : thank you so much for your reply! (Here is the corresponding stackoverflow question: https://stackoverflow.com/questions/65679523/r-obtaining-rules-from-a-function) . Your help is greatly Appreciated!

Thank you for your reply! ________________________________ From: Beth Atkinson Sent: January 13, 2021 2:16 PM To: bethatkinson/rpart Cc: swaheera ; Mention Subject: Re: [bethatkinson/rpart] Obtaining "Decision Rules" from rpart trees...