Re: [R] error in plotting model from kernlab
Hi
As I said I have no experience with kernlab but I can read in manual:
"probabilities matrix of class probabilities (one column for each class and one
row for each input)"
from which I understand that pred is matrix, which should have the same number
of rows as df$cons but several columns. And matrix is a vector with dimensions
what means that it is column times longer than df$cons, hence it is longer than
df$cons.
Plotting error suggeststs that ksvc object has to be classification object and
> type = "C-bsvc",
is not the same as "C-svc".
Cheers
Petr
> -Original Message-
> From: Luigi Marongiu
> Sent: Tuesday, January 8, 2019 4:40 PM
> To: PIKAL Petr
> Cc: r-help
> Subject: Re: [R] error in plotting model from kernlab
>
> Hi,
> the maintainer hasn't answered yet. The problem with 'acc' is that yes the
> objects are not of the same length but they should be: according to the
> manual,
> ' table(pred, df$cons)' would return a 2x2 matrix of the results. This is not
> the
> case, so there is a problem with the model -- that is why there is no plotting
> either -- even if an object of class ksvm had been created.
>
> On Tue, Jan 8, 2019 at 4:12 PM PIKAL Petr wrote:
> >
> > Hi
> >
> > I cannot help you with kernlab
> >
> > > > pred = predict(mod, df, type = "probabilities") acc =
> > > > table(pred, df$cons)
> > > Error in table(pred, df$cons) : all arguments must have the same
> > > length which again is weird since mod, df and df$cons are made from
> > > the same dataframe.
> >
> > Why not check length of those objects?
> >
> > length(pred)
> > length(df$cons)
> >
> > > > plot(mod, data = df)
> > > > kernlab::plot(mod, data = df)
> > > but I get this error:
> > >
> > > Error in .local(x, ...) :
> > > Only plots of classification ksvm objects supported
> > >
> >
> > seems to me selfexplanatory. What did maintainer said about it?
> >
> > Cheers
> > Petr
> >
> >
> > > -Original Message-
> > > From: R-help On Behalf Of Luigi
> > > Marongiu
> > > Sent: Monday, January 7, 2019 1:26 PM
> > > To: r-help
> > > Subject: [R] error in plotting model from kernlab
> > >
> > > Dear all,
> > > I have a set of data in this form:
> > > > str
> > > 'data.frame': 1574 obs. of 14 variables:
> > > $ serial: int 12751 14157 7226 15663 11088 10464 1003 10427 11934
> > > 3999 ...
> > > $ plate : int 43 46 22 50 38 37 3 37 41 11 ...
> > > $ well : int 79 333 314 303 336 96 235 59 30 159 ...
> > > $ sample: int 266 295 151 327 231 218 21 218 249 84 ...
> > > $ target: chr "HEV 2-AI5IQWR" "Dientamoeba fragilis-AIHSPMK"
> > > "Astro
> > > 2 Liu-AI20UKB" "C difficile GDH-AIS086J" ...
> > > $ ori.ct: num 0 33.5 0 0 0 ...
> > > $ ct.out: int 0 1 0 0 0 0 0 1 0 0 ...
> > > $ mr: num -0.002 0.109 0.002 0 0.001 0.006 0.015 0.119 0.003 0.004
> > > ...
> > > $ fcn : num 44.54 36.74 6.78 43.09 44.87 ...
> > > $ mr.out: int 0 1 0 0 0 0 0 1 0 0 ...
> > > $ oper.a: int 0 1 0 0 0 0 0 1 0 0 ...
> > > $ oper.b: int 0 1 0 0 0 0 0 1 0 0 ...
> > > $ oper.c: int 0 1 0 0 0 0 0 1 0 0 ...
> > > $ cons : int 0 1 0 0 0 0 0 1 0 0 ...
> > > from which I have selected two numerical variables correspondig to x
> > > and y in a Cartesian plane and one outcome variable (z):
> > > > df = subset(t.data, select = c(mr, fcn, cons)) df$cons =
> > > > factor(c("negative", "positive"))
> > > > head(df)
> > > mr fcn cons
> > > 1 -0.002 44.54 negative
> > > 2 0.109 36.74 positive
> > > 3 0.002 6.78 negative
> > > 4 0.000 43.09 positive
> > > 5 0.001 44.87 negative
> > > 6 0.006 2.82 positive
> > >
> > > I created an SVM the method with the KERNLAB package with:
> > > > mod = ksvm(cons ~ mr+fcn, # i prefer it to the more canonical "."
> > > > but the
> > > outcome is the same
> > > data = df,
> > > type = "C-bsvc",
> > > kernel = "rbfdot",
> > > kpar = "automatic",
> > > C = 10,
> > > prob.model = TRUE)
> > >
> > > > mod
> > > Support Vector
Re: [R] error in plotting model from kernlab
Hi,
the maintainer hasn't answered yet. The problem with 'acc' is that yes
the objects are not of the same length but they should be: according
to the manual, ' table(pred, df$cons)' would return a 2x2 matrix of
the results. This is not the case, so there is a problem with the
model -- that is why there is no plotting either -- even if an object
of class ksvm had been created.
On Tue, Jan 8, 2019 at 4:12 PM PIKAL Petr wrote:
>
> Hi
>
> I cannot help you with kernlab
>
> > > pred = predict(mod, df, type = "probabilities")
> > > acc = table(pred, df$cons)
> > Error in table(pred, df$cons) : all arguments must have the same length
> > which again is weird since mod, df and df$cons are made from the same
> > dataframe.
>
> Why not check length of those objects?
>
> length(pred)
> length(df$cons)
>
> > > plot(mod, data = df)
> > > kernlab::plot(mod, data = df)
> > but I get this error:
> >
> > Error in .local(x, ...) :
> > Only plots of classification ksvm objects supported
> >
>
> seems to me selfexplanatory. What did maintainer said about it?
>
> Cheers
> Petr
>
>
> > -Original Message-
> > From: R-help On Behalf Of Luigi Marongiu
> > Sent: Monday, January 7, 2019 1:26 PM
> > To: r-help
> > Subject: [R] error in plotting model from kernlab
> >
> > Dear all,
> > I have a set of data in this form:
> > > str
> > 'data.frame': 1574 obs. of 14 variables:
> > $ serial: int 12751 14157 7226 15663 11088 10464 1003 10427 11934 3999
> > ...
> > $ plate : int 43 46 22 50 38 37 3 37 41 11 ...
> > $ well : int 79 333 314 303 336 96 235 59 30 159 ...
> > $ sample: int 266 295 151 327 231 218 21 218 249 84 ...
> > $ target: chr "HEV 2-AI5IQWR" "Dientamoeba fragilis-AIHSPMK" "Astro
> > 2 Liu-AI20UKB" "C difficile GDH-AIS086J" ...
> > $ ori.ct: num 0 33.5 0 0 0 ...
> > $ ct.out: int 0 1 0 0 0 0 0 1 0 0 ...
> > $ mr: num -0.002 0.109 0.002 0 0.001 0.006 0.015 0.119 0.003 0.004 ...
> > $ fcn : num 44.54 36.74 6.78 43.09 44.87 ...
> > $ mr.out: int 0 1 0 0 0 0 0 1 0 0 ...
> > $ oper.a: int 0 1 0 0 0 0 0 1 0 0 ...
> > $ oper.b: int 0 1 0 0 0 0 0 1 0 0 ...
> > $ oper.c: int 0 1 0 0 0 0 0 1 0 0 ...
> > $ cons : int 0 1 0 0 0 0 0 1 0 0 ...
> > from which I have selected two numerical variables correspondig to x
> > and y in a Cartesian plane and one outcome variable (z):
> > > df = subset(t.data, select = c(mr, fcn, cons))
> > > df$cons = factor(c("negative", "positive"))
> > > head(df)
> > mr fcn cons
> > 1 -0.002 44.54 negative
> > 2 0.109 36.74 positive
> > 3 0.002 6.78 negative
> > 4 0.000 43.09 positive
> > 5 0.001 44.87 negative
> > 6 0.006 2.82 positive
> >
> > I created an SVM the method with the KERNLAB package with:
> > > mod = ksvm(cons ~ mr+fcn, # i prefer it to the more canonical "." but the
> > outcome is the same
> > data = df,
> > type = "C-bsvc",
> > kernel = "rbfdot",
> > kpar = "automatic",
> > C = 10,
> > prob.model = TRUE)
> >
> > > mod
> > Support Vector Machine object of class "ksvm"
> >
> > SV type: C-bsvc (classification)
> > parameter : cost C = 10
> >
> > Gaussian Radial Basis kernel function.
> > Hyperparameter : sigma = 42.0923201429106
> >
> > Number of Support Vectors : 1439
> >
> > Objective Function Value : -12873.45
> > Training error : 0.39263
> > Probability model included.
> >
> > First of all, I am not sure if the model worked because 1439 support
> > vectors out of 1574 data points means that over 90% of the data is
> > required to fix the hyperplane. this does not look like a model but a
> > patch. Secondly, the prediction is rubbish -- but this is another
> > story -- and when I try to create a confusion table of the processed
> > data I get:
> > > pred = predict(mod, df, type = "probabilities")
> > > acc = table(pred, df$cons)
> > Error in table(pred, df$cons) : all arguments must have the same length
> > which again is weird since mod, df and df$cons are made from the same
> > dataframe.
> >
> > Coming to the actual error, I tried to plot the model with:
> > > plot(mod, data = df)
> > > kernlab::plot(mod, data = df)
> > but I get this error:
> >
> > Error in .local(x, ...) :
> > Only plots of classification ksvm objects supported
> >
> > Would you know what I am missing?
> > Thank you
> > --
> > Best regards,
> > Luigi
> >
> > __
> > R-help@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.
> Osobní údaje: Informace o zpracování a ochraně osobních údajů obchodních
> partnerů PRECHEZA a.s. jsou zveřejněny na:
> https://www.precheza.cz/zasady-ochrany-osobnich-udaju/ | Information about
> processing and protection of business partner’s personal data are available
> on website: https://www.p
Re: [R] error in plotting model from kernlab
Hi
I cannot help you with kernlab
> > pred = predict(mod, df, type = "probabilities")
> > acc = table(pred, df$cons)
> Error in table(pred, df$cons) : all arguments must have the same length
> which again is weird since mod, df and df$cons are made from the same
> dataframe.
Why not check length of those objects?
length(pred)
length(df$cons)
> > plot(mod, data = df)
> > kernlab::plot(mod, data = df)
> but I get this error:
>
> Error in .local(x, ...) :
> Only plots of classification ksvm objects supported
>
seems to me selfexplanatory. What did maintainer said about it?
Cheers
Petr
> -Original Message-
> From: R-help On Behalf Of Luigi Marongiu
> Sent: Monday, January 7, 2019 1:26 PM
> To: r-help
> Subject: [R] error in plotting model from kernlab
>
> Dear all,
> I have a set of data in this form:
> > str
> 'data.frame': 1574 obs. of 14 variables:
> $ serial: int 12751 14157 7226 15663 11088 10464 1003 10427 11934 3999
> ...
> $ plate : int 43 46 22 50 38 37 3 37 41 11 ...
> $ well : int 79 333 314 303 336 96 235 59 30 159 ...
> $ sample: int 266 295 151 327 231 218 21 218 249 84 ...
> $ target: chr "HEV 2-AI5IQWR" "Dientamoeba fragilis-AIHSPMK" "Astro
> 2 Liu-AI20UKB" "C difficile GDH-AIS086J" ...
> $ ori.ct: num 0 33.5 0 0 0 ...
> $ ct.out: int 0 1 0 0 0 0 0 1 0 0 ...
> $ mr: num -0.002 0.109 0.002 0 0.001 0.006 0.015 0.119 0.003 0.004 ...
> $ fcn : num 44.54 36.74 6.78 43.09 44.87 ...
> $ mr.out: int 0 1 0 0 0 0 0 1 0 0 ...
> $ oper.a: int 0 1 0 0 0 0 0 1 0 0 ...
> $ oper.b: int 0 1 0 0 0 0 0 1 0 0 ...
> $ oper.c: int 0 1 0 0 0 0 0 1 0 0 ...
> $ cons : int 0 1 0 0 0 0 0 1 0 0 ...
> from which I have selected two numerical variables correspondig to x
> and y in a Cartesian plane and one outcome variable (z):
> > df = subset(t.data, select = c(mr, fcn, cons))
> > df$cons = factor(c("negative", "positive"))
> > head(df)
> mr fcn cons
> 1 -0.002 44.54 negative
> 2 0.109 36.74 positive
> 3 0.002 6.78 negative
> 4 0.000 43.09 positive
> 5 0.001 44.87 negative
> 6 0.006 2.82 positive
>
> I created an SVM the method with the KERNLAB package with:
> > mod = ksvm(cons ~ mr+fcn, # i prefer it to the more canonical "." but the
> outcome is the same
> data = df,
> type = "C-bsvc",
> kernel = "rbfdot",
> kpar = "automatic",
> C = 10,
> prob.model = TRUE)
>
> > mod
> Support Vector Machine object of class "ksvm"
>
> SV type: C-bsvc (classification)
> parameter : cost C = 10
>
> Gaussian Radial Basis kernel function.
> Hyperparameter : sigma = 42.0923201429106
>
> Number of Support Vectors : 1439
>
> Objective Function Value : -12873.45
> Training error : 0.39263
> Probability model included.
>
> First of all, I am not sure if the model worked because 1439 support
> vectors out of 1574 data points means that over 90% of the data is
> required to fix the hyperplane. this does not look like a model but a
> patch. Secondly, the prediction is rubbish -- but this is another
> story -- and when I try to create a confusion table of the processed
> data I get:
> > pred = predict(mod, df, type = "probabilities")
> > acc = table(pred, df$cons)
> Error in table(pred, df$cons) : all arguments must have the same length
> which again is weird since mod, df and df$cons are made from the same
> dataframe.
>
> Coming to the actual error, I tried to plot the model with:
> > plot(mod, data = df)
> > kernlab::plot(mod, data = df)
> but I get this error:
>
> Error in .local(x, ...) :
> Only plots of classification ksvm objects supported
>
> Would you know what I am missing?
> Thank you
> --
> Best regards,
> Luigi
>
> __
> R-help@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.
Osobní údaje: Informace o zpracování a ochraně osobních údajů obchodních
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https://www.precheza.cz/zasady-ochrany-osobnich-udaju/ | Information about
processing and protection of business partner’s personal data are available on
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained,
Re: [R] error in plotting model from kernlab
Sorry but I don't understand the questions. I sent this question to
R-help, not to an individual. I will use the REPLY TO ALL function
when replying, apologies if I missed before. The question is related
to an R package so I placed to the R community.
On Mon, Jan 7, 2019 at 5:47 PM Jeff Newmiller wrote:
>
> a) When re-posting a question, whether on the same or different forums, it is
> best practice (netiquette) to link to or reply to the earlier question. [1]
>
> b) Note the guidance in the Posting Guide:
>
> For questions about functions in standard packages distributed with R (see
> the FAQ Add-on packages in R), ask questions on R-help.
> If the question relates to a contributed package , e.g., one downloaded from
> CRAN, try contacting the package maintainer first. You can also use
> find("functionname") and packageDescription("packagename") to find this
> information. Only send such questions to R-help or R-devel if you get no
> reply or need further assistance. This applies to both requests for help and
> to bug reports.
>
> You have not communicated whether you have followed this recommendation.
>
> [1] https://stat.ethz.ch/pipermail/r-help/2018-December/461010.html
>
> On January 7, 2019 4:26:20 AM PST, Luigi Marongiu
> wrote:
> >Dear all,
> >I have a set of data in this form:
> >> str
> >'data.frame': 1574 obs. of 14 variables:
> >$ serial: int 12751 14157 7226 15663 11088 10464 1003 10427 11934 3999
> >...
> > $ plate : int 43 46 22 50 38 37 3 37 41 11 ...
> > $ well : int 79 333 314 303 336 96 235 59 30 159 ...
> > $ sample: int 266 295 151 327 231 218 21 218 249 84 ...
> > $ target: chr "HEV 2-AI5IQWR" "Dientamoeba fragilis-AIHSPMK" "Astro
> >2 Liu-AI20UKB" "C difficile GDH-AIS086J" ...
> > $ ori.ct: num 0 33.5 0 0 0 ...
> > $ ct.out: int 0 1 0 0 0 0 0 1 0 0 ...
> >$ mr: num -0.002 0.109 0.002 0 0.001 0.006 0.015 0.119 0.003 0.004
> >...
> > $ fcn : num 44.54 36.74 6.78 43.09 44.87 ...
> > $ mr.out: int 0 1 0 0 0 0 0 1 0 0 ...
> > $ oper.a: int 0 1 0 0 0 0 0 1 0 0 ...
> > $ oper.b: int 0 1 0 0 0 0 0 1 0 0 ...
> > $ oper.c: int 0 1 0 0 0 0 0 1 0 0 ...
> > $ cons : int 0 1 0 0 0 0 0 1 0 0 ...
> >from which I have selected two numerical variables correspondig to x
> >and y in a Cartesian plane and one outcome variable (z):
> >> df = subset(t.data, select = c(mr, fcn, cons))
> >> df$cons = factor(c("negative", "positive"))
> >> head(df)
> > mr fcn cons
> >1 -0.002 44.54 negative
> >2 0.109 36.74 positive
> >3 0.002 6.78 negative
> >4 0.000 43.09 positive
> >5 0.001 44.87 negative
> >6 0.006 2.82 positive
> >
> >I created an SVM the method with the KERNLAB package with:
> >> mod = ksvm(cons ~ mr+fcn, # i prefer it to the more canonical "." but
> >the outcome is the same
> >data = df,
> >type = "C-bsvc",
> >kernel = "rbfdot",
> >kpar = "automatic",
> >C = 10,
> >prob.model = TRUE)
> >
> >> mod
> >Support Vector Machine object of class "ksvm"
> >
> >SV type: C-bsvc (classification)
> > parameter : cost C = 10
> >
> >Gaussian Radial Basis kernel function.
> > Hyperparameter : sigma = 42.0923201429106
> >
> >Number of Support Vectors : 1439
> >
> >Objective Function Value : -12873.45
> >Training error : 0.39263
> >Probability model included.
> >
> >First of all, I am not sure if the model worked because 1439 support
> >vectors out of 1574 data points means that over 90% of the data is
> >required to fix the hyperplane. this does not look like a model but a
> >patch. Secondly, the prediction is rubbish -- but this is another
> >story -- and when I try to create a confusion table of the processed
> >data I get:
> >> pred = predict(mod, df, type = "probabilities")
> >> acc = table(pred, df$cons)
> >Error in table(pred, df$cons) : all arguments must have the same length
> >which again is weird since mod, df and df$cons are made from the same
> >dataframe.
> >
> >Coming to the actual error, I tried to plot the model with:
> >> plot(mod, data = df)
> >> kernlab::plot(mod, data = df)
> >but I get this error:
> >
> >Error in .local(x, ...) :
> > Only plots of classification ksvm objects supported
> >
> >Would you know what I am missing?
> >Thank you
>
> --
> Sent from my phone. Please excuse my brevity.
--
Best regards,
Luigi
__
R-help@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.
Re: [R] error in plotting model from kernlab
a) When re-posting a question, whether on the same or different forums, it is
best practice (netiquette) to link to or reply to the earlier question. [1]
b) Note the guidance in the Posting Guide:
For questions about functions in standard packages distributed with R (see the
FAQ Add-on packages in R), ask questions on R-help.
If the question relates to a contributed package , e.g., one downloaded from
CRAN, try contacting the package maintainer first. You can also use
find("functionname") and packageDescription("packagename") to find this
information. Only send such questions to R-help or R-devel if you get no reply
or need further assistance. This applies to both requests for help and to bug
reports.
You have not communicated whether you have followed this recommendation.
[1] https://stat.ethz.ch/pipermail/r-help/2018-December/461010.html
On January 7, 2019 4:26:20 AM PST, Luigi Marongiu
wrote:
>Dear all,
>I have a set of data in this form:
>> str
>'data.frame': 1574 obs. of 14 variables:
>$ serial: int 12751 14157 7226 15663 11088 10464 1003 10427 11934 3999
>...
> $ plate : int 43 46 22 50 38 37 3 37 41 11 ...
> $ well : int 79 333 314 303 336 96 235 59 30 159 ...
> $ sample: int 266 295 151 327 231 218 21 218 249 84 ...
> $ target: chr "HEV 2-AI5IQWR" "Dientamoeba fragilis-AIHSPMK" "Astro
>2 Liu-AI20UKB" "C difficile GDH-AIS086J" ...
> $ ori.ct: num 0 33.5 0 0 0 ...
> $ ct.out: int 0 1 0 0 0 0 0 1 0 0 ...
>$ mr: num -0.002 0.109 0.002 0 0.001 0.006 0.015 0.119 0.003 0.004
>...
> $ fcn : num 44.54 36.74 6.78 43.09 44.87 ...
> $ mr.out: int 0 1 0 0 0 0 0 1 0 0 ...
> $ oper.a: int 0 1 0 0 0 0 0 1 0 0 ...
> $ oper.b: int 0 1 0 0 0 0 0 1 0 0 ...
> $ oper.c: int 0 1 0 0 0 0 0 1 0 0 ...
> $ cons : int 0 1 0 0 0 0 0 1 0 0 ...
>from which I have selected two numerical variables correspondig to x
>and y in a Cartesian plane and one outcome variable (z):
>> df = subset(t.data, select = c(mr, fcn, cons))
>> df$cons = factor(c("negative", "positive"))
>> head(df)
> mr fcn cons
>1 -0.002 44.54 negative
>2 0.109 36.74 positive
>3 0.002 6.78 negative
>4 0.000 43.09 positive
>5 0.001 44.87 negative
>6 0.006 2.82 positive
>
>I created an SVM the method with the KERNLAB package with:
>> mod = ksvm(cons ~ mr+fcn, # i prefer it to the more canonical "." but
>the outcome is the same
>data = df,
>type = "C-bsvc",
>kernel = "rbfdot",
>kpar = "automatic",
>C = 10,
>prob.model = TRUE)
>
>> mod
>Support Vector Machine object of class "ksvm"
>
>SV type: C-bsvc (classification)
> parameter : cost C = 10
>
>Gaussian Radial Basis kernel function.
> Hyperparameter : sigma = 42.0923201429106
>
>Number of Support Vectors : 1439
>
>Objective Function Value : -12873.45
>Training error : 0.39263
>Probability model included.
>
>First of all, I am not sure if the model worked because 1439 support
>vectors out of 1574 data points means that over 90% of the data is
>required to fix the hyperplane. this does not look like a model but a
>patch. Secondly, the prediction is rubbish -- but this is another
>story -- and when I try to create a confusion table of the processed
>data I get:
>> pred = predict(mod, df, type = "probabilities")
>> acc = table(pred, df$cons)
>Error in table(pred, df$cons) : all arguments must have the same length
>which again is weird since mod, df and df$cons are made from the same
>dataframe.
>
>Coming to the actual error, I tried to plot the model with:
>> plot(mod, data = df)
>> kernlab::plot(mod, data = df)
>but I get this error:
>
>Error in .local(x, ...) :
> Only plots of classification ksvm objects supported
>
>Would you know what I am missing?
>Thank you
--
Sent from my phone. Please excuse my brevity.
__
R-help@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.
