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$assert(xs) :
Assertion on 'xs' failed: The parameter 'C' can only be set if the
following condition is met 'type {eps-svr, eps-bsvr}'. Instead the
parameter value for 'type'
Thanks a lot, Milne and Patrick.
I am going to change the values, hopefully the error message will disappear.
Warm regards
On Tue, Dec 29, 2020 at 5:53 PM Patrick (Malone Quantitative) <
mal...@malonequantitative.com> wrote:
> Likely, yes. Your error message says k must be at least 1, so search
Likely, yes. Your error message says k must be at least 1, so searching
below 1 is probably your issue.
Also, logically, zero nearest neighbors doesn't seem to make a lot of sense.
Pat
On Tue, Dec 29, 2020 at 11:01 AM Neha gupta
wrote:
> Thank you for your response.
>
> Are you certain that k
Thank you for your response.
Are you certain that k = 0 is a legitimate setting?
Since, the default value of k is 1, I wanted to search between the values
of 0 to 3.
Milne, Do you mean I have to provide both the lower and upper bounds
greater than 1 in order to get rid of this error?
On Tue, D
I am using mlr3 'fast nearest neighbor' leaner i.e. fnnIts parameter is 'k'
which has a default value of 1. When I use tuningusing random search, I set the
parameter of k as: lower= 0, upper=3But it gives an error messageError in
self$assert(xs) : Assertion on 'xs' failed: k: Element 1 is not >
I am using mlr3 'fast nearest neighbor' leaner i.e. fnn
Its parameter is 'k' which has a default value of 1. When I use tuning
using random search, I set the parameter of k as: lower= 0, upper=3
But it gives an error message
Error in self$assert(xs) :
Assertion on 'xs' failed: k: Element 1 is
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