MLSS - BML lecture - discriminative classification example

lectures/Discriminative Classification.jl

@@ -34,7 +34,7 @@ using Random, Plots, LaTeXStrings
 using MarkdownLiteral: @mdx
 
 # ╔═╡ 616e84d7-063d-4d9d-99e4-56aecf3c7ee4
-using Distributions, ExponentialFamily, LinearAlgebra, LogExpFunctions, StatsFuns, BayesBase, Optim
+using Distributions, ExponentialFamily, LinearAlgebra, LogExpFunctions, StatsFuns, BayesBase, Optim, StableRNGs
 
 # ╔═╡ 25eefb10-d294-11ef-0734-2daf18636e8e
 title("Discriminative Classification")
@@ -74,7 +74,7 @@ Our task will be the same as in the preceding class on (generative) classificati
 
 # ╔═╡ 4ceede48-a4d5-446b-bb34-26cec4af357a
 begin
-	N_bond = @bindname N Slider(9:200; default=120, show_value=true)
+	N_bond = @bindname N Slider(8:200; default=120, show_value=true)
 end
 
 # ╔═╡ 7e7cab21-09ab-4d06-9716-ab7864b229ab
@@ -452,7 +452,7 @@ Note that we get a full predictive posterior distribution over the assignment of
 
 # ╔═╡ 98ef7093-f8ed-4a44-a153-0a64ab483f65
 md"""
-## Implementation Issues
+## Implementation
 """
 
 # ╔═╡ 0045e569-dc3c-4998-86da-9d96f599c599
@@ -680,24 +680,24 @@ md"""
 
 # ╔═╡ fcec3c3a-8b0b-4dfd-b010-66abbf330069
 function generate_dataset(N::Int64)
-	Random.seed!(1234)
+	rng = StableRNG(984289)
     # Generate dataset {(x1,y1),...,(xN,yN)}
     # x is a 2d feature vector [x1;x2]
     # y ∈ {false,true} is a binary class label
     # p(x|y) is multi-modal (mixture of uniform and Gaussian distributions)
 	# srand(123)
     X = Matrix{Float64}(undef,2,N); y = Vector{Bool}(undef,N)
     for n=1:N
-        if (y[n]=(rand()>0.6)) # p(y=true) = 0.6
+        if (y[n]=(rand(rng)>0.6)) # p(y=true) = 0.6
             # Sample class 1 conditional distribution
-            if rand()<0.5
-                X[:,n] = [6.0; 0.5] .* rand(2) .+ [3.0; 6.0]
+            if rand(rng)<0.5
+                X[:,n] = [6.0; 0.5] .* rand(rng, 2) .+ [3.0; 6.0]
             else
-                X[:,n] = sqrt(0.5) * randn(2) .+ [5.5, 0.0]
+                X[:,n] = sqrt(0.5) * randn(rng, 2) .+ [5.5, 0.0]
             end
         else
             # Sample class 2 conditional distribution
-            X[:,n] = randn(2) .+ [1., 4.]
+            X[:,n] = randn(rng, 2) .+ [1., 4.]
         end
     end
 
@@ -843,6 +843,7 @@ MarkdownLiteral = "736d6165-7244-6769-4267-6b50796e6954"
 Optim = "429524aa-4258-5aef-a3af-852621145aeb"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
 StatsFuns = "4c63d2b9-4356-54db-8cca-17b64c39e42c"
 
 [compat]
@@ -854,17 +855,18 @@ LaTeXStrings = "~1.4.0"
 LogExpFunctions = "~0.3.29"
 MarkdownLiteral = "~0.1.2"
 Optim = "~1.13.2"
-Plots = "~1.40.17"
+Plots = "~1.40.20"
+StableRNGs = "~1.0.4"
 StatsFuns = "~1.5.0"
 """
 
 # ╔═╡ 00000000-0000-0000-0000-000000000002
 PLUTO_MANIFEST_TOML_CONTENTS = """
 # This file is machine-generated - editing it directly is not advised
 
-julia_version = "1.12.1"
+julia_version = "1.12.2"
 manifest_format = "2.0"
-project_hash = "6c3dd68af2e626ed33e0c26a2dd1c4e83dc100b4"
+project_hash = "88b4b8c9292999e875bc97e1e761ba61613bdfda"
 
 [[deps.ADTypes]]
 git-tree-sha1 = "27cecae79e5cc9935255f90c53bb831cc3c870d7"
@@ -1237,7 +1239,7 @@ version = "0.7.16"
 [[deps.Downloads]]
 deps = ["ArgTools", "FileWatching", "LibCURL", "NetworkOptions"]
 uuid = "f43a241f-c20a-4ad4-852c-f6b1247861c6"
-version = "1.6.0"
+version = "1.7.0"
 
 [[deps.EnumX]]
 git-tree-sha1 = "bddad79635af6aec424f53ed8aad5d7555dc6f00"
@@ -1562,7 +1564,7 @@ version = "0.6.4"
 [[deps.LibCURL_jll]]
 deps = ["Artifacts", "LibSSH2_jll", "Libdl", "OpenSSL_jll", "Zlib_jll", "nghttp2_jll"]
 uuid = "deac9b47-8bc7-5906-a0fe-35ac56dc84c0"
-version = "8.11.1+1"
+version = "8.15.0+0"
 
 [[deps.LibGit2]]
 deps = ["LibGit2_jll", "NetworkOptions", "Printf", "SHA"]
@@ -1749,7 +1751,7 @@ version = "1.5.0"
 [[deps.OpenSSL_jll]]
 deps = ["Artifacts", "Libdl"]
 uuid = "458c3c95-2e84-50aa-8efc-19380b2a3a95"
-version = "3.5.1+0"
+version = "3.5.4+0"
 
 [[deps.OpenSpecFun_jll]]
 deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "Libdl"]
@@ -2047,9 +2049,9 @@ version = "2.6.1"
 
 [[deps.StableRNGs]]
 deps = ["Random"]
-git-tree-sha1 = "95af145932c2ed859b63329952ce8d633719f091"
+git-tree-sha1 = "4f96c596b8c8258cc7d3b19797854d368f243ddc"
 uuid = "860ef19b-820b-49d6-a774-d7a799459cd3"
-version = "1.0.3"
+version = "1.0.4"
 
 [[deps.StaticArrays]]
 deps = ["LinearAlgebra", "PrecompileTools", "Random", "StaticArraysCore"]
@@ -2453,9 +2455,9 @@ uuid = "8e850ede-7688-5339-a07c-302acd2aaf8d"
 version = "1.64.0+1"
 
 [[deps.p7zip_jll]]
-deps = ["Artifacts", "Libdl"]
+deps = ["Artifacts", "CompilerSupportLibraries_jll", "Libdl"]
 uuid = "3f19e933-33d8-53b3-aaab-bd5110c3b7a0"
-version = "17.5.0+2"
+version = "17.7.0+0"
 
 [[deps.x264_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl"]
@@ -2545,12 +2547,12 @@ version = "1.9.2+0"
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-# ╠═fcec3c3a-8b0b-4dfd-b010-66abbf330069
+# ╟─fcec3c3a-8b0b-4dfd-b010-66abbf330069
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-# ╠═1bfac9c5-e5cf-4a70-b077-11bb00cb1482
-# ╠═fd908bf5-71a1-4ae8-8416-cc1fdf084dcb
+# ╟─1bfac9c5-e5cf-4a70-b077-11bb00cb1482
+# ╟─fd908bf5-71a1-4ae8-8416-cc1fdf084dcb
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