Add error when there are zero possible engines when fitting a model

[EmilHvitfeldt]

This PR aims to close #634.

library(parsnip)

cubist_rules() %>%
  fit(mpg ~ ., data = mtcars)
#> Error: No engines where loaded for `cubist_rules`. Please load extension package that provides one.

pls() %>%
  set_mode("regression") %>%
  fit(mpg ~ ., data = mtcars)
#> Error: No engines where loaded for `pls`. Please load extension package that provides one.

linear_reg() %>%
  fit(mpg ~ ., data = mtcars)
#> parsnip model object
#> 
#> 
#> Call:
#> stats::lm(formula = mpg ~ ., data = data)
#> 
#> Coefficients:
#> (Intercept)          cyl         disp           hp         drat           wt  
#>    12.30337     -0.11144      0.01334     -0.02148      0.78711     -3.71530  
#>        qsec           vs           am         gear         carb  
#>     0.82104      0.31776      2.52023      0.65541     -0.19942

library(plsmod)

pls() %>%
  set_mode("regression") %>%
  fit(mpg ~ ., data = mtcars)
#> parsnip model object
#> 
#> 
#> Call:
#>  mixOmics::spls(X = x, Y = y, ncomp = ncomp, keepX = keepX) 
#> 
#>  sPLS with a 'regression' mode with 10 sPLS components. 
#>  You entered data X of dimensions: 32 10 
#>  You entered data Y of dimensions: 32 1 
#> 
#>  Selection of [10] [10] [10] [10] [10] [10] [10] [10] [10] [10] variables on each of the sPLS components on the X data set. 
#>  Selection of [1] [1] [1] [1] [1] [1] [1] [1] [1] [1] variables on each of the sPLS components on the Y data set. 
#> 
#>  Main numerical outputs: 
#>  -------------------- 
#>  loading vectors: see object$loadings 
#>  variates: see object$variates 
#>  variable names: see object$names 
#> 
#>  Functions to visualise samples: 
#>  -------------------- 
#>  plotIndiv, plotArrow 
#> 
#>  Functions to visualise variables: 
#>  -------------------- 
#>  plotVar, plotLoadings, network, cim

^{Created on 2022-01-26 by the reprex package (v2.0.1)}

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