I am using mlr3 'fast nearest neighbor' leaner i.e. fnnIts parameter is 'k' which has a default value of 1. When I use tuningusing random search, I set the parameter of k as: lower= 0, upper=3But it gives an error messageError in self$assert(xs) : Assertion on 'xs' failed: k: Element 1 is not >= 1.I have tried different values but the error remains.Warm regards [[alternative HTML version deleted]] I know absolutely nothing about the specific statistical tools being used here, but:? In several nearest neighbor routines, the parameter k refers to the number of nearest neighbors to be considered (in some computation).? In that case, k must be at least 1, which is what the cited error message seems to be claiming.? Are you certain that k = 0 is a legitimate setting? - T. Arthur Milne
Error in setting the parameter values of k
5 messages · T. A. Milne, Patrick (Malone Quantitative), Neha gupta
Thank you for your response. Are you certain that k = 0 is a legitimate setting? Since, the default value of k is 1, I wanted to search between the values of 0 to 3. Milne, Do you mean I have to provide both the lower and upper bounds greater than 1 in order to get rid of this error?
On Tue, Dec 29, 2020 at 4:50 PM T. A. Milne <milneta at tuta.io> wrote:
I am using mlr3 'fast nearest neighbor' leaner i.e. fnnIts parameter is 'k' which has a default value of 1. When I use tuningusing random search, I set the parameter of k as: lower= 0, upper=3But it gives an error messageError in self$assert(xs) : Assertion on 'xs' failed: k: Element 1 is not >= 1.I have tried different values but the error remains.Warm regards [[alternative HTML version deleted]] I know absolutely nothing about the specific statistical tools being used here, but: In several nearest neighbor routines, the parameter k refers to the number of nearest neighbors to be considered (in some computation). In that case, k must be at least 1, which is what the cited error message seems to be claiming. Are you certain that k = 0 is a legitimate setting? - T. Arthur Milne
Likely, yes. Your error message says k must be at least 1, so searching below 1 is probably your issue. Also, logically, zero nearest neighbors doesn't seem to make a lot of sense. Pat On Tue, Dec 29, 2020 at 11:01 AM Neha gupta <neha.bologna90 at gmail.com> wrote:
Thank you for your response. Are you certain that k = 0 is a legitimate setting? Since, the default value of k is 1, I wanted to search between the values of 0 to 3. Milne, Do you mean I have to provide both the lower and upper bounds greater than 1 in order to get rid of this error? On Tue, Dec 29, 2020 at 4:50 PM T. A. Milne <milneta at tuta.io> wrote:
I am using mlr3 'fast nearest neighbor' leaner i.e. fnnIts parameter is 'k' which has a default value of 1. When I use tuningusing random
search, I
set the parameter of k as: lower= 0, upper=3But it gives an error messageError in self$assert(xs) : Assertion on 'xs' failed: k: Element 1 is not >= 1.I have tried different values but the error remains.Warm regards [[alternative HTML version deleted]] I know absolutely nothing about the specific statistical tools being used here, but: In several nearest neighbor routines, the parameter k refers to the
number
of nearest neighbors to be considered (in some computation). In that
case,
k must be at least 1, which is what the cited error message seems to be claiming. Are you certain that k = 0 is a legitimate setting? - T. Arthur Milne
[[alternative HTML version deleted]]
______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Patrick S. Malone, Ph.D., Malone Quantitative NEW Service Models: http://malonequantitative.com He/Him/His [[alternative HTML version deleted]]
Thanks a lot, Milne and Patrick. I am going to change the values, hopefully the error message will disappear. Warm regards On Tue, Dec 29, 2020 at 5:53 PM Patrick (Malone Quantitative) <
malone at malonequantitative.com> wrote:
Likely, yes. Your error message says k must be at least 1, so searching below 1 is probably your issue. Also, logically, zero nearest neighbors doesn't seem to make a lot of sense. Pat On Tue, Dec 29, 2020 at 11:01 AM Neha gupta <neha.bologna90 at gmail.com> wrote:
Thank you for your response. Are you certain that k = 0 is a legitimate setting? Since, the default value of k is 1, I wanted to search between the values of 0 to 3. Milne, Do you mean I have to provide both the lower and upper bounds greater than 1 in order to get rid of this error? On Tue, Dec 29, 2020 at 4:50 PM T. A. Milne <milneta at tuta.io> wrote:
I am using mlr3 'fast nearest neighbor' leaner i.e. fnnIts parameter is 'k' which has a default value of 1. When I use tuningusing random
search, I
set the parameter of k as: lower= 0, upper=3But it gives an error messageError in self$assert(xs) : Assertion on 'xs' failed: k: Element
1
is not >= 1.I have tried different values but the error remains.Warm regards [[alternative HTML version deleted]] I know absolutely nothing about the specific statistical tools being
used
here, but: In several nearest neighbor routines, the parameter k refers to the
number
of nearest neighbors to be considered (in some computation). In that
case,
k must be at least 1, which is what the cited error message seems to be claiming. Are you certain that k = 0 is a legitimate setting? - T. Arthur Milne
[[alternative HTML version deleted]]
______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
-- Patrick S. Malone, Ph.D., Malone Quantitative NEW Service Models: http://malonequantitative.com He/Him/His
Hello, I am sorry but after settings the value of C between 1 and 7, I get
the following error message now:
Error in self$assert(xs) :
Assertion on 'xs' failed: The parameter 'C' can only be set if the
following condition is met 'type <U+2208> {eps-svr, eps-bsvr}'. Instead the
parameter value for 'type' is not set at all. Try setting 'type' to a value
that satisfies the condition.
I have set the parameter values as following:
search_space = paradox::ParamSet$new(
params = list(paradox::ParamInt$new("C", lower = 1, upper = 7)))
On Tue, Dec 29, 2020 at 6:36 PM Neha gupta <neha.bologna90 at gmail.com> wrote:
Thanks a lot, Milne and Patrick. I am going to change the values, hopefully the error message will disappear. Warm regards On Tue, Dec 29, 2020 at 5:53 PM Patrick (Malone Quantitative) < malone at malonequantitative.com> wrote:
Likely, yes. Your error message says k must be at least 1, so searching below 1 is probably your issue. Also, logically, zero nearest neighbors doesn't seem to make a lot of sense. Pat On Tue, Dec 29, 2020 at 11:01 AM Neha gupta <neha.bologna90 at gmail.com> wrote:
Thank you for your response. Are you certain that k = 0 is a legitimate setting? Since, the default value of k is 1, I wanted to search between the values of 0 to 3. Milne, Do you mean I have to provide both the lower and upper bounds greater than 1 in order to get rid of this error? On Tue, Dec 29, 2020 at 4:50 PM T. A. Milne <milneta at tuta.io> wrote:
I am using mlr3 'fast nearest neighbor' leaner i.e. fnnIts parameter is 'k' which has a default value of 1. When I use tuningusing random
search, I
set the parameter of k as: lower= 0, upper=3But it gives an error messageError in self$assert(xs) : Assertion on 'xs' failed: k:
Element 1
is not >= 1.I have tried different values but the error remains.Warm regards [[alternative HTML version deleted]] I know absolutely nothing about the specific statistical tools being
used
here, but: In several nearest neighbor routines, the parameter k refers to the
number
of nearest neighbors to be considered (in some computation). In that
case,
k must be at least 1, which is what the cited error message seems to be claiming. Are you certain that k = 0 is a legitimate setting? - T. Arthur Milne
[[alternative HTML version deleted]]
______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
-- Patrick S. Malone, Ph.D., Malone Quantitative NEW Service Models: http://malonequantitative.com He/Him/His