[R] contrasts can be applied only to factors with 2 or more levels

Patrick (Malone Quantitative) m@|one @end|ng |rom m@|onequ@nt|t@t|ve@com
Fri Dec 20 22:20:34 CET 2019


As the Posting Guide directs, please make all replies to the list.

Basically, you need to inspect your data. Using "~ ." adds everything
in the dataframe that's not elsewhere in the function as predictors.
Check the descriptive statistics on every one (variance/standard
deviation for numeric data, table for string/factor).

On Fri, Dec 20, 2019 at 3:32 PM javed khan <javedbtk111 using gmail.com> wrote:
>
> Hi Patrick
>
> I have no idea about this type of error. Is it a categorical predictor? How to find variability?
>
> Thanks
>
> On Fri, Dec 20, 2019 at 9:08 PM Patrick (Malone Quantitative) <malone using malonequantitative.com> wrote:
>>
>> Seems self-explanatory. It sounds like one of your predictors has no
>> variability.
>>
>> On Fri, Dec 20, 2019 at 3:01 PM javed khan <javedbtk111 using gmail.com> wrote:
>> >
>> > I am using the folowing code and it give me the error message like
>> >
>> > " contrasts can be applied only to factors with 2 or more levels".
>> >
>> > What could be the problem
>> >
>> > d=read.csv("Result.csv")
>> > index <- createDataPartition(log10(d$Results), p = .70,list = FALSE)
>> > tr <- d[index, ]
>> > ts <- d[-index, ]
>> > index_2 <- createFolds(log10(tr$Results), returnTrain = TRUE, list = TRUE)
>> > ctrl <- trainControl(method = "cv", index = index_2)
>> >
>> > set.seed(30218)
>> >
>> > grid_search <- train(log10(Results) ~ ., data = tr,
>> >                      method = "svmRadial",
>> >
>> >                      tuneLength = 8,
>> >                      metric = "MAE",
>> >                      preProc = c("center", "scale", "zv"),
>> >                      trControl = ctrl)
>> >
>> >         [[alternative HTML version deleted]]
>> >
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