Merge pull request #82 from JuliaAI/dev

For a 0.1.5 release

Project.toml

@@ -1,7 +1,7 @@
 name = "Imbalance"
 uuid = "c709b415-507b-45b7-9a3d-1767c89fde68"
 authors = ["Essam Wisam <[email protected]>", "Anthony Blaom <[email protected]> and contributors"]
-version = "0.1.4"
+version = "0.1.5"
 
 
 [deps]

src/oversampling_methods/random_oversample/interface_mlj.jl

@@ -91,7 +91,11 @@ $((COMMON_DOCS["RNG"]))
 
 # Transform Inputs
 
-$((COMMON_DOCS["INPUTS"]))
+- `X`: A matrix of real numbers or a table with element [scitypes](https://juliaai.github.io/ScientificTypes.jl/) that subtype `Union{Finite, Infinite}`. 
+     Elements in nominal columns should subtype `Finite` (i.e., have [scitype](https://juliaai.github.io/ScientificTypes.jl/) `OrderedFactor` or `Multiclass`) and
+     elements in continuous columns should subtype `Infinite` (i.e., have [scitype](https://juliaai.github.io/ScientificTypes.jl/) `Count` or `Continuous`).
+
+- `y`: An abstract vector of labels (e.g., strings) that correspond to the observations in `X`
 
 # Transform Outputs
 

src/oversampling_methods/random_oversample/random_oversample.jl

@@ -33,7 +33,11 @@ Naively oversample a dataset by randomly repeating existing observations with re
 
 # Positional Arguments
 
-$(COMMON_DOCS["INPUTS"])
+- `X`: A matrix of real numbers or a table with element [scitypes](https://juliaai.github.io/ScientificTypes.jl/) that subtype `Union{Finite, Infinite}`. 
+     Elements in nominal columns should subtype `Finite` (i.e., have [scitype](https://juliaai.github.io/ScientificTypes.jl/) `OrderedFactor` or `Multiclass`) and
+     elements in continuous columns should subtype `Infinite` (i.e., have [scitype](https://juliaai.github.io/ScientificTypes.jl/) `Count` or `Continuous`).
+
+- `y`: An abstract vector of labels (e.g., strings) that correspond to the observations in `X`
 
 # Keyword Arguments
 

src/oversampling_methods/random_walk/interface_mlj.jl

@@ -97,7 +97,7 @@ $((COMMON_DOCS["RNG"]))
 
 # Transform Inputs
 
-- `X`: A matrix of floats or a table with element [scitypes](https://juliaai.github.io/ScientificTypes.jl/) 
+- `X`: A table with element [scitypes](https://juliaai.github.io/ScientificTypes.jl/) 
      that subtype `Union{Finite, Infinite}`. Elements in nominal columns should subtype `Finite` 
      (i.e., have [scitype](https://juliaai.github.io/ScientificTypes.jl/) `OrderedFactor` or `Multiclass`) and
 	 elements in continuous columns should subtype `Infinite` (i.e., have 

src/oversampling_methods/smoten/interface_mlj.jl

@@ -61,14 +61,14 @@ MMI.metadata_model(
     input_scitype = Tuple{
                         Union{
                             Table(Finite),
-                            AbstractMatrix{Finite}
+                            AbstractMatrix{<:Finite}
                         }, 
                         AbstractVector
                     },
     output_scitype = Tuple{
         Union{
             Table(Finite),
-            AbstractMatrix{Finite}
+            AbstractMatrix{<:Finite}
         }, 
         AbstractVector
     },
@@ -77,7 +77,7 @@ MMI.metadata_model(
 
 function MMI.transform_scitype(s::SMOTEN)
     return Tuple{
-        Union{Table(Finite),AbstractMatrix{Finite}},
+        Union{Table(Finite),AbstractMatrix{<:Finite}},
         AbstractVector{<:Finite},
     }
 end
@@ -119,7 +119,11 @@ $((COMMON_DOCS["RNG"]))
 
 # Transform Inputs
 
-$((COMMON_DOCS["INPUTS"]))
+- `X`: A matrix of integers or a table with element [scitypes](https://juliaai.github.io/ScientificTypes.jl/) that subtype `Finite`. 
+     That is, for table inputs each column should have either `OrderedFactor` or `Multiclass` as the element [scitype](https://juliaai.github.io/ScientificTypes.jl/).
+
+- `y`: An abstract vector of labels (e.g., strings) that correspond to the observations in `X`
+
 
 # Transform Outputs
 

src/oversampling_methods/smotenc/interface_mlj.jl

@@ -121,7 +121,11 @@ $((COMMON_DOCS["RNG"]))
 
 # Transform Inputs
 
-$((COMMON_DOCS["INPUTS"]))
+- `X`: A table with element [scitypes](https://juliaai.github.io/ScientificTypes.jl/) that subtype `Union{Finite, Infinite}`. 
+     Elements in nominal columns should subtype `Finite` (i.e., have [scitype](https://juliaai.github.io/ScientificTypes.jl/) `OrderedFactor` or `Multiclass`) and
+     elements in continuous columns should subtype `Infinite` (i.e., have [scitype](https://juliaai.github.io/ScientificTypes.jl/) `Count` or `Continuous`).
+
+- `y`: An abstract vector of labels (e.g., strings) that correspond to the observations in `X`
 
 # Transform Outputs
 

src/undersampling_methods/random_undersample/interface_mlj.jl

@@ -100,7 +100,11 @@ $((COMMON_DOCS["RNG"]))
 
 # Transform Inputs
 
-$((COMMON_DOCS["INPUTS"]))
+- `X`: A matrix of real numbers or a table with element [scitypes](https://juliaai.github.io/ScientificTypes.jl/) that subtype `Union{Finite, Infinite}`. 
+     Elements in nominal columns should subtype `Finite` (i.e., have [scitype](https://juliaai.github.io/ScientificTypes.jl/) `OrderedFactor` or `Multiclass`) and
+     elements in continuous columns should subtype `Infinite` (i.e., have [scitype](https://juliaai.github.io/ScientificTypes.jl/) `Count` or `Continuous`).
+
+- `y`: An abstract vector of labels (e.g., strings) that correspond to the observations in `X`
 
 # Transform Outputs
 

src/undersampling_methods/random_undersample/random_undersample.jl

@@ -34,7 +34,11 @@ Naively undersample a dataset by randomly deleting existing observations.
 
 # Positional Arguments
 
-$(COMMON_DOCS["INPUTS"])
+- `X`: A matrix of real numbers or a table with element [scitypes](https://juliaai.github.io/ScientificTypes.jl/) that subtype `Union{Finite, Infinite}`. 
+     Elements in nominal columns should subtype `Finite` (i.e., have [scitype](https://juliaai.github.io/ScientificTypes.jl/) `OrderedFactor` or `Multiclass`) and
+     elements in continuous columns should subtype `Infinite` (i.e., have [scitype](https://juliaai.github.io/ScientificTypes.jl/) `Count` or `Continuous`).
+
+- `y`: An abstract vector of labels (e.g., strings) that correspond to the observations in `X`
 
 # Keyword Arguments