Fix links

Author: abhro

src/composition/learning_networks/nodes.jl

@@ -277,7 +277,7 @@ function _formula(stream, X::Node, depth, indent)
     if X.machine !== nothing
         print(stream, crind(indent + length(operation_name) - anti))
         printstyled(IOContext(stream, :color=>SHOW_COLOR[]),
-#                        handle(X.machine),
+                        #handle(X.machine),
                         X.machine,
                         bold=SHOW_COLOR[])
         n_args == 0 || print(stream, ", ")

src/data/datasets.jl

@@ -199,7 +199,7 @@ function load_smarket()
 end
 
 """Load a well-known sunspot time series (table with one column).
-[https://www.sws.bom.gov.au/Educational/2/3/6]](https://www.sws.bom.gov.au/Educational/2/3/6)
+<https://www.sws.bom.gov.au/Educational/2/3/6>
 """
 load_sunspots() = load_dataset("sunspots.csv", COERCE_SUNSPOTS)
 
@@ -250,9 +250,10 @@ macro load_crabs()
     end
 end
 
-""" Load S&P Stock Market dataset, as used in (An Introduction to
-Statistical Learning with applications in
-R)[https://rdrr.io/cran/ISLR/man/Smarket.html](https://rdrr.io/cran/ISLR/man/Smarket.html),
+"""
+Load S&P Stock Market dataset, as used in
+[An Introduction to Statistical Learning with applications in
+R](https://rdrr.io/cran/ISLR/man/Smarket.html),
 by Witten et al (2013), Springer-Verlag, New York."""
 macro load_smarket()
     quote

src/data/datasets_synthetic.jl

@@ -21,12 +21,12 @@ Internal function to  finalize the `make_*` functions.
 function finalize_Xy(X, y, shuffle, as_table, eltype, rng; clf::Bool=true)
     # Shuffle the rows if required
     if shuffle
-                X, y = shuffle_rows(X, y; rng=rng)
-        end
-        if eltype != Float64
-                X = convert.(eltype, X)
-        end
-        # return as matrix if as_table=false
+        X, y = shuffle_rows(X, y; rng=rng)
+    end
+    if eltype != Float64
+        X = convert.(eltype, X)
+    end
+    # return as matrix if as_table=false
     as_table || return X, y
     clf && return MLJBase.table(X), categorical(y)
     if length(size(y)) > 1

src/machines.jl

@@ -1073,8 +1073,7 @@ predict(predict_only_mach, X)
     general purpose serialization formats, can allow for arbitrary code
     execution during loading. This means it is possible for someone
     to use a JLS file that looks like a serialized MLJ machine as a
-    [Trojan
-    horse](https://en.wikipedia.org/wiki/Trojan_horse_(computing)).
+    [Trojan horse](https://en.wikipedia.org/wiki/Trojan_horse_(computing)).
 
 See also [`serializable`](@ref), [`machine`](@ref).
 

src/resampling.jl

@@ -536,8 +536,8 @@ and the corresponding estimates, aggregated over all train/test pairs, are recor
 When displayed, a `PerformanceEvaluation` object includes a value under the heading
 `1.96*SE`, derived from the standard error of the `per_fold` entries. This value is
 suitable for constructing a formal 95% confidence interval for the given
-`measurement`. Such intervals should be interpreted with caution. See, for example, Bates
-et al.  [(2021)](https://arxiv.org/abs/2104.00673).
+`measurement`. Such intervals should be interpreted with caution. See, for example, [Bates
+et al.  (2021)](https://arxiv.org/abs/2104.00673).
 
 ### Fields
 

src/show.jl

@@ -347,7 +347,7 @@ function _recursive_show(stream::IO, object::MLJType, current_depth, depth)
         print(stream, "#"^current_depth, " ")
         show(stream, object)
         println(stream, ": ")
-#        println(stream)
+        # println(stream)
         if isempty(fields)
             println(stream)
             return
@@ -358,10 +358,10 @@ function _recursive_show(stream::IO, object::MLJType, current_depth, depth)
             print(stream, fld_string)
             if isdefined(object, fld)
                 _show(stream, getproperty(object, fld))
-                #           println(stream)
+                # println(stream)
             else
                 println(stream, "(undefined)")
-                #           println(stream)
+                # println(stream)
             end
         end
         println(stream)