Improve documentation and add Quickstart vignette

[johnfrombluff]

Firstly, thank you for your hard work on this software.

From reading the Examples in the help page for xspline I saw you could use it with a DALEX explainer

# using DALEX
library(DALEX)
xs_iris_explainer <- explain(rf_iris)
xs_iris <- xspline(rf_iris)
summary(xs_iris)
plot(xs_iris, "Sepal.Length")

Although it appears that the documentation has a mistake? xspline is called with rf_iris as its argument, shouldn't that be xs_iris_explainer ?

I tried to use it on my own data, but ran into problems:

> exp_all <- explain(money_ibg_all_mlr$learner,
+                    data    = rm_dv(money_ibg_all_dat),
+                    y       = get_dv(money_ibg_all_dat),
+                    label   = "All variables",
+                    verbose = TRUE)
Preparation of a new explainer is initiated
  -> model label       :  All variables 
  -> data              :  399  rows  188  cols 
  -> data              :  tibble converted into a data.frame 
  -> target variable   :  399  values 
  -> predict function  :  yhat.LearnerClassif  will be used (  default  )
  -> predicted values  :  No value for predict function target column. (  default  )
  -> model_info        :  package mlr3 , ver. 0.12.0 , task classification (  default  ) 
  -> predicted values  :  numerical, min =  0.03240848 , mean =  0.3114011 , max =  0.9021189  
  -> residual function :  difference between y and yhat (  default  )
  -> residuals         :  numerical, min =  0.2578514 , mean =  0.9868445 , max =  1.885718  
  A new explainer has been created!  
> class(exp_all)
[1] "explainer"
> xspline(exp_all)
Error in get_model_data(object, data, env) : Data must be provided.
> 

Is there anything obviously wrong with my code, or is this a bug in the documentation? (Or something else ...?)

Also, on the Readme.md page it says to go to the "xsplainer page" for more info, but that link is circular. Are there any vignettes or any other information about how to use the package, other than the help pages for each function?

Thanks again,

John