restored assert and removed Bayesregressor from the atomic_models list

Author: pasq-cat

Project.toml

@@ -10,6 +10,7 @@ ComputationalResources = "ed09eef8-17a6-5b46-8889-db040fac31e3"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
 InferOpt = "4846b161-c94e-4150-8dac-c7ae193c601f"
+LaplaceRedux = "c52c1a26-f7c5-402b-80be-ba1e638ad478"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
 MLJEnsembles = "50ed68f4-41fd-4504-931a-ed422449fee0"
@@ -30,6 +31,7 @@ ComputationalResources = "0.3"
 Distributions = "0.25.109"
 Flux = "0.13, 0.14"
 InferOpt = "0.6.1"
+LaplaceRedux = "1.0.2"
 LinearAlgebra = " 1.9, 1.10"
 MLJBase = "0.20, 0.21, 1"
 MLJEnsembles = "0.3.3, 0.4"

src/conformal_models/conformal_models.jl

@@ -126,7 +126,7 @@ const tested_atomic_models = Dict(
         :nearest_neighbor => :(@load KNNRegressor pkg = NearestNeighborModels),
         :decision_tree_regressor => :(@load DecisionTreeRegressor pkg = DecisionTree),
         :random_forest_regressor => :(@load RandomForestRegressor pkg = DecisionTree),
-        :bayesregressor => :(@load BayesRegressor pkg = LaplaceRedux),
+        #:bayesregressor => :(@load BayesRegressor pkg = LaplaceRedux),
         # :light_gbm => :(@load LGBMRegressor pkg = LightGBM),
         # :neural_network => :(@load NeuralNetworkRegressor pkg = MLJFlux),
         # :symbolic_regression => (@load SRRegressor pkg = SymbolicRegression),

src/conformal_models/inductive_bayes_regression.jl

@@ -1,4 +1,5 @@
 
+using LaplaceRedux: LaplaceRegression
 @doc raw"""
 The `BayesRegressor` is the simplest approach to Inductive Conformalized Bayes. As explained in https://arxiv.org/abs/2107.07511,
 the  conformal score is  defined as the opposite of the probability of observing y given x : `` s= -P(Y|X) ``. Once the treshold ``\hat{q}`` is chosen, The credible interval is then
@@ -19,6 +20,7 @@ function BayesRegressor(
     heuristic::Function=conformal_bayes_score,
     train_ratio::AbstractFloat=0.5,
 )
+    @assert typeof(model) == LaplaceRegression "Model must be of type Laplace"
     return BayesRegressor(model, coverage, nothing, heuristic, train_ratio)
 end