R help - Dec 2019 - all the MAE metric values are missing (Error message)

I am using the following code to tune the 4 parameters of Gradient Boosting
algorithm using Simulated annealing (optim). When I run the program, after
few seconds it stops and displays the following error:

I point out here that the same code works for RF ( mtry parameter) and SVM
(cost and sigma parameters). So, I guess the problem should be in the 4
parameters of GBM

Something is wrong; all the MAE metric values are missing:
      RMSE        Rsquared        MAE
 Min.   : NA   Min.   : NA   Min.   : NA
 1st Qu.: NA   1st Qu.: NA   1st Qu.: NA
 Median : NA   Median : NA   Median : NA
 Mean   :NaN   Mean   :NaN   Mean   :NaN
 3rd Qu.: NA   3rd Qu.: NA   3rd Qu.: NA
 Max.   : NA   Max.   : NA   Max.   : NA
 NA's   :1     NA's   :1     NA's   :1

Code is here/// If you need the  dataset, I can attach in the email

d=readARFF("dat.arff")   ///DATA IS REGRESSION BASED

index <- createDataPartition(log10(d$Price), p = .70,list = FALSE)
tr <- d[index, ]
ts <- d[-index, ]

index_2 <- createFolds(log10(tr$Price), returnTrain = TRUE, list = TRUE)
ctrl <- trainControl(method = "cv", index = index_2)

obj <- function(param, maximize = FALSE) {
  mod <- train(log10(Price) ~ ., data = tr,
               method = "gbm",
               preProc = c("center", "scale",
"zv"),
               metric = "MAE",
               trControl = ctrl,
       //HERE IN tuneGrid WHEN I USE PARAMETERS FOR SVM    AND RF, IT
WORKS, BUT FOR GBM, IT DOES NOT WORK

               tuneGrid = data.frame(n.trees = 10^(param[1]),
interaction.depth = 10^(param[2]),
                                     shrinkage=10^(param[3]),
n.minobsinnode=10^(param[4])))

  if(maximize)
    -getTrainPerf(mod)[, "TrainMAE"] else
      getTrainPerf(mod)[, "TrainMAE"]
}
num_mods <- 50

## Simulated annealing from base R

/// I JUST USED HERE SOME INITIAL POINTS OF THE 4 PARAMETERS OF GBM

san_res <- optim(par = c(10,1,0.1,1), fn = obj, method = "SANN",
                 control = list(maxit = num_mods))
san_res

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-- 

David.

On 12/22/19 9:15 AM, Neha gupta wrote:
> I am using the following code to tune the 4 parameters of Gradient Boosting
> algorithm using Simulated annealing (optim). When I run the program, after
> few seconds it stops and displays the following error:
>
> I point out here that the same code works for RF ( mtry parameter) and SVM
> (cost and sigma parameters). So, I guess the problem should be in the 4
> parameters of GBM
>
> Something is wrong; all the MAE metric values are missing:
>        RMSE        Rsquared        MAE
>   Min.   : NA   Min.   : NA   Min.   : NA
>   1st Qu.: NA   1st Qu.: NA   1st Qu.: NA
>   Median : NA   Median : NA   Median : NA
>   Mean   :NaN   Mean   :NaN   Mean   :NaN
>   3rd Qu.: NA   3rd Qu.: NA   3rd Qu.: NA
>   Max.   : NA   Max.   : NA   Max.   : NA
>   NA's   :1     NA's   :1     NA's   :1
>
> Code is here/// If you need the  dataset, I can attach in the email
>
> d=readARFF("dat.arff")   ///DATA IS REGRESSION BASED
>
> index <- createDataPartition(log10(d$Price), p = .70,list = FALSE)
> tr <- d[index, ]
> ts <- d[-index, ]
>
> index_2 <- createFolds(log10(tr$Price), returnTrain = TRUE, list = TRUE)
> ctrl <- trainControl(method = "cv", index = index_2)
>
> obj <- function(param, maximize = FALSE) {
>    mod <- train(log10(Price) ~ ., data = tr,
>                 method = "gbm",
>                 preProc = c("center", "scale",
"zv"),
>                 metric = "MAE",
>                 trControl = ctrl,
>         //HERE IN tuneGrid WHEN I USE PARAMETERS FOR SVM    AND RF, IT
> WORKS, BUT FOR GBM, IT DOES NOT WORK
>
>                 tuneGrid = data.frame(n.trees = 10^(param[1]),
> interaction.depth = 10^(param[2]),
>                                       shrinkage=10^(param[3]),
> n.minobsinnode=10^(param[4])))
>
>    if(maximize)
>      -getTrainPerf(mod)[, "TrainMAE"] else
>        getTrainPerf(mod)[, "TrainMAE"]
> }
> num_mods <- 50
>
> ## Simulated annealing from base R
>
> /// I JUST USED HERE SOME INITIAL POINTS OF THE 4 PARAMETERS OF GBM
>
> san_res <- optim(par = c(10,1,0.1,1), fn = obj, method =
"SANN",
>                   control = list(maxit = num_mods))
> san_res
>
> 	[[alternative HTML version deleted]]
>
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Hi Neha,
The error message looks suspicious, as it refers to "all the MAEs"
while there is only one NA value in the summary. I would carefully
check the object that you are passing to san_res.

Jim

On Mon, Dec 23, 2019 at 4:17 AM Neha gupta <neha.bologna90 at gmail.com>
wrote:
>
> I am using the following code to tune the 4 parameters of Gradient Boosting
> algorithm using Simulated annealing (optim). When I run the program, after
> few seconds it stops and displays the following error:
>
> I point out here that the same code works for RF ( mtry parameter) and SVM
> (cost and sigma parameters). So, I guess the problem should be in the 4
> parameters of GBM
>
> Something is wrong; all the MAE metric values are missing:
>       RMSE        Rsquared        MAE
>  Min.   : NA   Min.   : NA   Min.   : NA
>  1st Qu.: NA   1st Qu.: NA   1st Qu.: NA
>  Median : NA   Median : NA   Median : NA
>  Mean   :NaN   Mean   :NaN   Mean   :NaN
>  3rd Qu.: NA   3rd Qu.: NA   3rd Qu.: NA
>  Max.   : NA   Max.   : NA   Max.   : NA
>  NA's   :1     NA's   :1     NA's   :1
>

Hi Jim

The objective function is passed to san_res where we have defined the 4
parameters of gbm and the values are initialized in san_res.

The output variable price has only three values: 0, 1, 2 (like categorical
values), so someone told me try to remove the log10 from the price.

I am not sure what to do, I spent two days but did not fix this issue.


On Sun, Dec 22, 2019 at 11:22 PM Jim Lemon <drjimlemon at gmail.com>
wrote:
> Hi Neha,
> The error message looks suspicious, as it refers to "all the
MAEs"
> while there is only one NA value in the summary. I would carefully
> check the object that you are passing to san_res.
>
> Jim
>
> On Mon, Dec 23, 2019 at 4:17 AM Neha gupta <neha.bologna90 at
gmail.com>
> wrote:
> >
> > I am using the following code to tune the 4 parameters of Gradient
> Boosting
> > algorithm using Simulated annealing (optim). When I run the program,
> after
> > few seconds it stops and displays the following error:
> >
> > I point out here that the same code works for RF ( mtry parameter) and
> SVM
> > (cost and sigma parameters). So, I guess the problem should be in the
4
> > parameters of GBM
> >
> > Something is wrong; all the MAE metric values are missing:
> >       RMSE        Rsquared        MAE
> >  Min.   : NA   Min.   : NA   Min.   : NA
> >  1st Qu.: NA   1st Qu.: NA   1st Qu.: NA
> >  Median : NA   Median : NA   Median : NA
> >  Mean   :NaN   Mean   :NaN   Mean   :NaN
> >  3rd Qu.: NA   3rd Qu.: NA   3rd Qu.: NA
> >  Max.   : NA   Max.   : NA   Max.   : NA
> >  NA's   :1     NA's   :1     NA's   :1
> >
>
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