Error when I try to predict class probabilities in R - caret

Question

I've build a model using caret. When the training was completed I got the following warning: Warning message: In train.default(x, y, weights = w, ...) : At least one of the class levels are not valid R variables names; This may cause errors if class probabilities are generated because the variables names will be converted to: X0, X1 The names of the variables are: ``` str(train) 'data.frame': 7395 obs. of 30 variables: $ alchemy_category : Factor w/ 13 levels "arts_entertainment",..: 2 8 6 6 11 6 1 6 3 8 ... $ alchemy_category_score : num 3737 2052 4801 3816 3179 ... $ avglinksize : num 2.06 3.68 2.38 1.54 2.68 ... $ commonlinkratio_1 : num 0.676 0.508 0.562 0.4 0.5 ... $ commonlinkratio_2 : num 0.206 0.289 0.322 0.1 0.222 ... $ commonlinkratio_3 : num 0.0471 0.2139 0.1202 0.0167 0.1235 ... $ commonlinkratio_4 : num 0.0235 0.1444 0.0426 0 0.0432 ... $ compression_ratio : num 0.444 0.469 0.525 0.481 0.446 ... $ embed_ratio : num 0 0 0 0 0 0 0 0 0 0 ... $ frameTagRatio : num 0.0908 0.09…

Accepted Answer

The answer is in bold at the top of your post =]

What are you modeling? Is it `alchemy_category`? The code only says `formula` and we can't see it.

When you ask for class probabilities, model predictions are a data frame with separate columns for each class/level. If `alchemy_category` doesn't have levels that are valid column names, `data.frame` converts then to valid names. That creates a problem because the code is looking for a specific name but the data frame as a different (but valid) name.

For example, if I had

```
> test <- factor(c("level1", "level 2")) 
> levels(test)
[1] "level 2" "level1" 
> make.names(levels(test))
[1] "level.2" "level1"
```

the code would be looking for "level 2" but there is only "level.2".

Error when I try to predict class probabilities in R - caret

Solution

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