fd-update

Author: tlienart

__site/__generated/A-composing-models.tar.gz

@@ -214,9 +214,9 @@ version = "1.0.0"
 
 [[deps.JLLWrappers]]
 deps = ["Preferences"]
-git-tree-sha1 = "642a199af8b68253517b80bd3bfd17eb4e84df6e"
+git-tree-sha1 = "22df5b96feef82434b07327e2d3c770a9b21e023"
 uuid = "692b3bcd-3c85-4b1f-b108-f13ce0eb3210"
-version = "1.3.0"
+version = "1.4.0"
 
 [[deps.JLSO]]
 deps = ["BSON", "CodecZlib", "FilePathsBase", "Memento", "Pkg", "Serialization"]
@@ -474,9 +474,9 @@ version = "1.2.2"
 
 [[deps.Requires]]
 deps = ["UUIDs"]
-git-tree-sha1 = "8f82019e525f4d5c669692772a6f4b0a58b06a6a"
+git-tree-sha1 = "838a3a4188e2ded87a4f9f184b4b0d78a1e91cb7"
 uuid = "ae029012-a4dd-5104-9daa-d747884805df"
-version = "1.2.0"
+version = "1.3.0"
 
 [[deps.Rmath]]
 deps = ["Random", "Rmath_jll"]
@@ -538,9 +538,9 @@ version = "1.0.0"
 
 [[deps.StaticArrays]]
 deps = ["LinearAlgebra", "Random", "Statistics"]
-git-tree-sha1 = "88a559da57529581472320892576a486fa2377b9"
+git-tree-sha1 = "2ae4fe21e97cd13efd857462c1869b73c9f61be3"
 uuid = "90137ffa-7385-5640-81b9-e52037218182"
-version = "1.3.1"
+version = "1.3.2"
 
 [[deps.StatisticalTraits]]
 deps = ["ScientificTypesBase"]

__site/__generated/A-composing-models/Manifest.toml

@@ -238,9 +238,9 @@ version = "1.0.0"
 
 [[deps.JLLWrappers]]
 deps = ["Preferences"]
-git-tree-sha1 = "642a199af8b68253517b80bd3bfd17eb4e84df6e"
+git-tree-sha1 = "22df5b96feef82434b07327e2d3c770a9b21e023"
 uuid = "692b3bcd-3c85-4b1f-b108-f13ce0eb3210"
-version = "1.3.0"
+version = "1.4.0"
 
 [[deps.JLSO]]
 deps = ["BSON", "CodecZlib", "FilePathsBase", "Memento", "Pkg", "Serialization"]
@@ -521,9 +521,9 @@ version = "1.2.2"
 
 [[deps.Requires]]
 deps = ["UUIDs"]
-git-tree-sha1 = "8f82019e525f4d5c669692772a6f4b0a58b06a6a"
+git-tree-sha1 = "838a3a4188e2ded87a4f9f184b4b0d78a1e91cb7"
 uuid = "ae029012-a4dd-5104-9daa-d747884805df"
-version = "1.2.0"
+version = "1.3.0"
 
 [[deps.Rmath]]
 deps = ["Random", "Rmath_jll"]

__site/__generated/A-ensembles-2.tar.gz

@@ -29,7 +29,7 @@ figure(figsize=(8,6))
 plot(curves.parameter_values, curves.measurements)
 ylabel("Root Mean Squared error", fontsize=16)
 xlabel("Number of trees", fontsize=16)
-xticks([10, 250, 500, 750, 1000], fontsize=14)
+xticks([10, 100, 250, 500, 750, 1000], fontsize=14)
 yticks(fontsize=14)
 
 forest.n = 150;
@@ -65,7 +65,7 @@ yticks(0.4:0.2:1, fontsize=12)
 ylabel("Bagging fraction", fontsize=14)
 
 ŷ = predict(m, X)
-rms(ŷ, y)
+@show rms(ŷ, y)
 
 # This file was generated using Literate.jl, https://github.com/fredrikekre/Literate.jl
 

__site/__generated/A-ensembles-2/Manifest.toml

@@ -139,7 +139,7 @@
     "plot(curves.parameter_values, curves.measurements)\n",
     "ylabel(\"Root Mean Squared error\", fontsize=16)\n",
     "xlabel(\"Number of trees\", fontsize=16)\n",
-    "xticks([10, 250, 500, 750, 1000], fontsize=14)\n",
+    "xticks([10, 100, 250, 500, 750, 1000], fontsize=14)\n",
     "yticks(fontsize=14)"
    ],
    "metadata": {},
@@ -150,7 +150,7 @@
    "source": [
     "\\figalt{RMS vs number of trees}{A-ensembles-2-curves.svg}\n",
     "\n",
-    "The curve is pretty noisy but let's just go for 150 trees:"
+    "Let's go for 150 trees"
    ],
    "metadata": {}
   },
@@ -270,7 +270,7 @@
    "cell_type": "code",
    "source": [
     "ŷ = predict(m, X)\n",
-    "rms(ŷ, y)"
+    "@show rms(ŷ, y)"
    ],
    "metadata": {},
    "execution_count": null

__site/__generated/A-ensembles-2/tutorial-raw.jl

@@ -58,12 +58,12 @@ figure(figsize=(8,6))
 plot(curves.parameter_values, curves.measurements)
 ylabel("Root Mean Squared error", fontsize=16)
 xlabel("Number of trees", fontsize=16)
-xticks([10, 250, 500, 750, 1000], fontsize=14)
+xticks([10, 100, 250, 500, 750, 1000], fontsize=14)
 yticks(fontsize=14)
 
 # \figalt{RMS vs number of trees}{A-ensembles-2-curves.svg}
 #
-# The curve is pretty noisy but let's just go for 150 trees:
+# Let's go for 150 trees
 
 forest.n = 150;
 
@@ -117,7 +117,7 @@ ylabel("Bagging fraction", fontsize=14)
 # For instance we could look at predictions on the whole dataset:
 
 ŷ = predict(m, X)
-rms(ŷ, y)
+@show rms(ŷ, y)
 
 # This file was generated using Literate.jl, https://github.com/fredrikekre/Literate.jl
 

__site/__generated/A-ensembles-2/tutorial.ipynb

@@ -232,9 +232,9 @@ version = "1.0.0"
 
 [[deps.JLLWrappers]]
 deps = ["Preferences"]
-git-tree-sha1 = "642a199af8b68253517b80bd3bfd17eb4e84df6e"
+git-tree-sha1 = "22df5b96feef82434b07327e2d3c770a9b21e023"
 uuid = "692b3bcd-3c85-4b1f-b108-f13ce0eb3210"
-version = "1.3.0"
+version = "1.4.0"
 
 [[deps.JLSO]]
 deps = ["BSON", "CodecZlib", "FilePathsBase", "Memento", "Pkg", "Serialization"]
@@ -509,9 +509,9 @@ version = "1.2.2"
 
 [[deps.Requires]]
 deps = ["UUIDs"]
-git-tree-sha1 = "8f82019e525f4d5c669692772a6f4b0a58b06a6a"
+git-tree-sha1 = "838a3a4188e2ded87a4f9f184b4b0d78a1e91cb7"
 uuid = "ae029012-a4dd-5104-9daa-d747884805df"
-version = "1.2.0"
+version = "1.3.0"
 
 [[deps.Rmath]]
 deps = ["Random", "Rmath_jll"]

__site/__generated/A-ensembles-2/tutorial.jl

@@ -35,6 +35,7 @@ r = range(atom,
 
 mach = machine(atom, X, y)
 
+figure()
 curve = learning_curve!(mach,
                         range=r,
                         measure=mav,
@@ -51,12 +52,12 @@ r = range(one_hundred_models,
 
 mach = machine(one_hundred_models, X, y)
 
+figure()
 curve = learning_curve!(mach,
                         range=r,
                         measure=mav,
                         resampling=CV(nfolds=9),
                         verbosity=0)
-
 plot(curve.parameter_values, curve.measurements)
 xlabel(curve.parameter_name)