I have achieved this use case by writing the following commands:
all_predictions <- data.frame(pid = testPFI$project_id, actual_delay =
testPFI$project_delay,lm_pred, tree_pred, best_tree_pred, rf_pred)
str(all_predictions)
all_pred <- sqldf("SELECT pid, actual_delay, ROUND(lm_pred,2) lm_pred,
Pls don't mind the typo in predict() functions for some of the models.
Sent from my iPhone
> On 11 May 2016, at 12:47 am, Muhammad Bilal
> wrote:
>
> Hi All,
>
>
> I have the following dataset:
>
>
>> str(pfi_v3)
> 'data.frame': 714 obs. of 8 variables:
>
Hi All,
I have the following dataset:
> str(pfi_v3)
'data.frame': 714 obs. of 8 variables:
$ project_id : int 1 2 3 4 5 6 7 8 9 10 ...
$ project_lat: num 51.4 51.5 52.2 51.5 53.5 ...
$ project_lon: num -0.642 -1.85 0.08 0.126 -1.392 ...
$ sector
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