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open Ast
(** summary(model) — returns a tidy summary DataFrame for native models.
For regression models this is coefficient-level output; for tree/ensemble
PMML models this falls back to model-level fit statistics. *)
(*
--# Model Summary
--#
--# Returns a tidy summary DataFrame for native models.
--#
--# @name summary
--# @param model :: Model The model object (e.g., from lm()).
--# @return :: Dict Tidy summary dictionary with `_tidy_df` and metadata.
--# @example
--# s = summary(model)
--# coefficients = s._tidy_df
--# @family stats
--# @seealso lm, fit_stats
--# @export
*)
let register env =
Env.add "summary"
(make_builtin ~name:"summary" 1 (fun args _env ->
match args with
| [VDict pairs] ->
let tidy_df = List.assoc_opt "_tidy_df" pairs in
let model_class = List.assoc_opt "class" pairs in
let model_type = List.assoc_opt "model_type" pairs in
let mining_function = List.assoc_opt "mining_function" pairs in
let family = List.assoc_opt "family" pairs in
let link = List.assoc_opt "link" pairs in
let summary_dict tidy_df_value extra_pairs =
VDict (
("_tidy_df", tidy_df_value) ::
(match model_class with Some v -> [("model_class", v)] | None -> []) @
(match model_type with Some v -> [("model_type", v)] | None -> []) @
(match mining_function with Some v -> [("mining_function", v)] | None -> []) @
extra_pairs @
[("class", VString "summary")]
)
in
(match tidy_df with
| Some ((VDataFrame _) as tidy_df_value) ->
summary_dict tidy_df_value
((match family with Some v -> [("family", v)] | None -> []) @
(match link with Some v -> [("link", v)] | None -> []))
| _ ->
(match Fit_stats.summary_metrics_for_model pairs with
| Some stats_df ->
summary_dict stats_df [("summary_type", VString "fit_stats")]
| None ->
Error.type_error "Function `summary` expects a native model object."))
| [VError _ as e] -> e
| _ ->
Error.type_error "Function `summary` expects a native model object."
))
env