bug fixes (describetask)

Author: codeboy5

FastTimeSeries/src/FastTimeSeries.jl

@@ -43,6 +43,7 @@ include("recipes.jl")
 
 const _tasks = Dict{String, Any}()
 include("tasks/classification.jl")
+include("tasks/regression.jl")
 
 function __init__()
     _registerrecipes()
@@ -54,5 +55,5 @@ function __init__()
 end
 
 export
-    TimeSeriesRow, TSClassificationSingle, TSPreprocessing, _ts2df
+    TimeSeriesRow, TSClassificationSingle, TSPreprocessing, TSRegression
 end

FastTimeSeries/src/container.jl

@@ -205,7 +205,7 @@ function _ts2df(
 
                                     char_num += 1
                                     num_this_dimension = 1
-                                    arr = Array{Float32, 2}(undef, num_dimensions, series_length)
+                                    arr = Array{Float64, 2}(undef, num_dimensions, series_length)
 
                                 else
 
@@ -333,7 +333,7 @@ function _ts2df(
         num_samples = length(instance_list)
         series_length = size(instance_list[1])[2]
 
-        data = Array{Float32, 3}(undef, num_samples, num_dimensions, series_length)
+        data = Array{Float64, 3}(undef, num_samples, num_dimensions, series_length)
 
         for sample in 1:num_samples
             data[sample, 1:end, 1:end] = instance_list[sample]

FastTimeSeries/src/recipes.jl

@@ -87,3 +87,11 @@ end
     sample = getobs(data, 1)
     @test checkblock(block, sample)
 end
+
+@testset "TimeSeriesDatasetRegression [recipe]" begin
+    path = load(datasets()["appliances_energy"])
+    recipe = TimeSeriesDatasetRecipe(train_file="AppliancesEnergy_TRAIN.ts", test_file="AppliancesEnergy_TEST.ts", regression = true);
+    data, block = Datasets.loadrecipe(recipe, path)
+    sample = getobs(data, 1)
+    @test checkblock(block, sample)
+end

FastTimeSeries/src/tasks/regression.jl

@@ -0,0 +1,27 @@
+"""
+    TSRegressionSingle
+
+Learning task for single-label time-series regression. Samples are standardized.
+"""
+
+function TSRegression(blocks::Tuple{<:TimeSeriesRow, <:Continuous}, data)
+    return SupervisedTask(
+        blocks,
+        (
+            setup(TSPreprocessing, blocks[1], data[1].table),
+        ),
+    )    
+end
+
+_tasks["tsregression"] = (
+    id = "timeseries/regression",
+    name = "Time-Series Regression",
+    constructor = TSRegression,
+    blocks = (TimeSeriesRow, Continuous),
+    category = "supervised",
+    description = """
+        Time-Series regression task where every time-series has a single 
+        regression label associated with it.
+        """,
+    package = @__MODULE__,
+)