Add missing docstrings

Author: juliohm

src/StatsLearnModels.jl

@@ -38,11 +38,11 @@ export
   GeneralizedLinearRegressor,
 
   # DecisionTree.jl
-  AdaBoostStumpClassifier,
   DecisionTreeClassifier,
-  RandomForestClassifier,
   DecisionTreeRegressor,
+  RandomForestClassifier,
   RandomForestRegressor,
+  AdaBoostStumpClassifier,
 
   # transform
   Learn

src/models/glm.jl

@@ -4,12 +4,33 @@
 
 abstract type GLMModel end
 
+"""
+    LinearRegressor(; kwargs...)
+
+Linear regression model.
+
+The `kwargs` are forwarded to the `GLM.lm` function
+from [GLM.jl](https://github.com/JuliaStats/GLM.jl).
+
+See also [`GeneralizedLinearRegressor`](@ref).
+"""
 struct LinearRegressor{K} <: GLMModel
   kwargs::K
 end
 
 LinearRegressor(; kwargs...) = LinearRegressor(values(kwargs))
 
+"""
+    GeneralizedLinearRegressor(dist, link; kwargs...)
+
+Generalized linear regression model with distribution `dist`
+from Distributions.jl and `link` function.
+
+The `kwargs` are forwarded to the `GLM.glm` function
+from [GLM.jl](https://github.com/JuliaStats/GLM.jl).
+
+See also [`LinearRegressor`](@ref).
+"""
 struct GeneralizedLinearRegressor{D<:UnivariateDistribution,L<:Union{GLM.Link,Nothing},K} <: GLMModel
   dist::D
   link::L

src/models/nn.jl

@@ -4,6 +4,16 @@
 
 abstract type NearestNeighborsModel end
 
+"""
+    KNNClassifier(k, metric=Euclidean(); leafsize=10, reorder=true)
+
+K-nearest neighbor classification model with `k` neighbors
+and `metric` from Distances.jl. Optionally, specify the
+`leafsize` and `reorder` options for the underlying trees in
+[NearestNeighbors.jl](https://github.com/KristofferC/NearestNeighbors.jl).
+
+See also [`KNNRegressor`](@ref).
+"""
 struct KNNClassifier{M<:Metric} <: NearestNeighborsModel
   k::Int
   metric::M
@@ -13,6 +23,16 @@ end
 
 KNNClassifier(k, metric=Euclidean(); leafsize=10, reorder=true) = KNNClassifier(k, metric, leafsize, reorder)
 
+"""
+    KNNRegressor(k, metric=Euclidean(); leafsize=10, reorder=true)
+
+K-nearest neighbor regression model with `k` neighbors
+and `metric` from Distances.jl. Optionally, specify the
+`leafsize` and `reorder` options for the underlying trees in
+[NearestNeighbors.jl](https://github.com/KristofferC/NearestNeighbors.jl).
+
+See also [`KNNClassifier`](@ref).
+"""
 struct KNNRegressor{M<:Metric} <: NearestNeighborsModel
   k::Int
   metric::M