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closing some issues
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‎A-model-tuning-hm.png

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‎A-model-tuning-hpt.svg

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‎ISL-lab-5-g1.svg

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‎ISL-lab-5-g3.svg

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‎__site/assets/data/categorical/code/output/ex1.res

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6-element CategoricalArray{String,1,UInt32}:
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6-element CategoricalArrays.CategoricalArray{String,1,UInt32}:
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"AA"
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"BB"
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"CC"

‎__site/assets/data/categorical/code/output/ex7.res

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6-element CategoricalArray{String,1,UInt32}:
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6-element CategoricalArrays.CategoricalArray{String,1,UInt32}:
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"high"
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"med"
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"low"

‎__site/assets/data/dataframe/code/output/ex10.res

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2×13 DataFrame
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2×13 DataFrames.DataFrame
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│ Row │ Crim │ Zn │ Indus │ Chas │ Rm │ Age │ Dis │ Rad │ Tax │ PTRatio │ Black │ LStat │ MedV │
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│ │ Float64 │ Float64 │ Float64 │ Int64 │ Float64 │ Float64 │ Float64 │ Int64 │ Int64 │ Float64 │ Float64 │ Float64 │ Float64 │
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├─────┼─────────┼─────────┼─────────┼───────┼─────────┼─────────┼─────────┼───────┼───────┼─────────┼─────────┼─────────┼─────────┤

‎__site/assets/data/dataframe/code/output/ex11.res

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2×2 DataFrame
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2×2 DataFrames.DataFrame
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│ Row │ Zn │ Indus │
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│ │ Float64 │ Float64 │
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├─────┼─────────┼─────────┤

‎__site/assets/data/dataframe/code/output/ex12.res

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│ Row │ variable │ min │ max │ mean │ median │ std │
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│ │ Symbol │ Real │ Real │ Float64 │ Float64 │ Float64 │
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├─────┼──────────┼─────────┼─────────┼──────────┼─────────┼──────────┤

‎__site/assets/data/dataframe/code/output/ex13.res

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│ Row │ variable │ mean │ median │ foo │
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│ │ Symbol │ Float64 │ Float64 │ Float64 │
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├─────┼──────────┼─────────┼─────────┼─────────┤

‎__site/assets/data/dataframe/code/output/ex17.res

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│ Row │ variable │ nmissing │
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│ │ Symbol │ Union… │
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├─────┼──────────┼──────────┤

‎__site/assets/data/dataframe/code/output/ex2.res

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DataFrame
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DataFrames.DataFrame

‎__site/assets/data/dataframe/code/output/ex20.res

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3×5 DataFrame
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3×5 DataFrames.DataFrame
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│ Row │ SepalLength │ SepalWidth │ PetalLength │ PetalWidth │ Species │
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│ │ Float64 │ Float64 │ Float64 │ Float64 │ Categorical… │
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├─────┼─────────────┼────────────┼─────────────┼────────────┼──────────────┤

‎__site/assets/data/dataframe/code/output/ex23.res

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5×4 DataFrame
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5×4 DataFrames.DataFrame
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│ Row │ variable │ min │ mean │ max │
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│ │ Symbol │ Any │ Union… │ Any │
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├─────┼─────────────┼────────┼────────┼────────┤

‎__site/assets/data/dataframe/code/output/ex24.res

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3×2 DataFrame
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3×2 DataFrames.DataFrame
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│ Row │ Species │ PetalLength_mean │
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│ │ Categorical… │ Float64 │
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├─────┼──────────────┼──────────────────┤

‎__site/assets/data/dataframe/code/output/ex25.res

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│ Row │ Species │ MPL │ SPL │
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│ │ Categorical… │ Float64 │ Float64 │
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├─────┼──────────────┼─────────┼──────────┤

‎__site/assets/data/dataframe/code/output/ex26.res

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│ Row │ Species │ SepalLength_std │ SepalWidth_std │ PetalLength_std │ PetalWidth_std │
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│ │ Categorical… │ Float64 │ Float64 │ Float64 │ Float64 │
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├─────┼──────────────┼─────────────────┼────────────────┼─────────────────┼────────────────┤

‎__site/assets/data/dataframe/code/output/ex4.res

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│ Row │ Crim │ Zn │ Indus │ Chas │ NOx │ Rm │ Age │ Dis │ Rad │ Tax │ PTRatio │ Black │ LStat │ MedV │
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│ │ Float64 │ Float64 │ Float64 │ Int64 │ Float64 │ Float64 │ Float64 │ Float64 │ Int64 │ Int64 │ Float64 │ Float64 │ Float64 │ Float64 │
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├─────┼─────────┼─────────┼─────────┼───────┼─────────┼─────────┼─────────┼─────────┼───────┼───────┼─────────┼─────────┼─────────┼─────────┤

‎__site/assets/data/dataframe/code/output/ex7.res

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│ Row │ Crim │ Zn │
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│ │ Float64 │ Float64 │
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├─────┼─────────┼─────────┤

‎__site/assets/data/dataframe/code/output/ex8.res

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│ Row │ Crim │ Zn │
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│ │ Float64 │ Float64 │
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├─────┼─────────┼─────────┤

‎__site/assets/data/dataframe/code/output/ex9.res

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│ Row │ Crim │ Zn │ Indus │
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│ │ Float64 │ Float64 │ Float64 │
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├─────┼─────────┼─────────┼─────────┤

‎__site/assets/data/loading/code/output/ex4.res

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DataFrames.DataFrame(AbstractArray{T,1} where T[
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│ Row │ col1 │ col2 │ col3 │ col4 │ col5 │ col6 │ col7 │ col8 │
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│ │ Missing │ Int64 │ Float64 │ Float64 │ String │ Dates.Date │ Dates.DateTime │ Bool │
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├─────┼─────────┼───────┼─────────┼─────────┼────────┼────────────┼─────────────────────┼──────┤
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│ 1 │ missing │ 1 │ 1.0 │ 1.0 │ one │ 2019-01-01 │ 2019-01-01T00:00:00 │ 1 │
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│ 2 │ missing │ 2 │ 2.0 │ 2.0 │ two │ 2019-01-02 │ 2019-01-02T00:00:00 │ 0 │
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│ 3 │ missing │ 3 │ 3.0 │ 3.14 │ three │ 2019-01-03 │ 2019-01-03T00:00:00 │ 1 │

‎__site/assets/data/loading/code/output/ex5.res

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DataFrames.DataFrame

‎__site/assets/data/loading/code/output/ex7.res

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│ Row │ CIC0 │ SM1_Dz │ GATS1i │ NdsCH │ NdssC │ MLOGP │ LC50 │
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│ │ Float64 │ Float64 │ Float64 │ Int64 │ Int64 │ Float64 │ Float64 │
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├─────┼─────────┼─────────┼─────────┼───────┼───────┼─────────┼─────────┤

‎__site/assets/data/loading/code/output/ex9.res

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│ Row │ Column1 │ Column2 │ Column3 │ Column4 │ Column5 │
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│ │ Int64 │ Int64⍰ │ Int64 │ Int64 │ Int64⍰ │
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├─────┼─────────┼─────────┼─────────┼─────────┼─────────┤

‎__site/assets/end-to-end/AMES/code/output/ex11.res

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Node @ 1…37 = predict(1…76, transform(9…41, 9…98))
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Node @ 1…43 = predict(1…92, transform(2…65, 1…28))

‎__site/assets/end-to-end/AMES/code/output/ex25.res

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3-element Array{MLJBase.NumericRange{MLJBase.Bounded,T,Symbol} where T,1}:
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NumericRange @ 8…14
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NumericRange @ 3…25
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NumericRange @ 4…51
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NumericRange @ 4…66
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NumericRange @ 2…80

‎__site/assets/end-to-end/AMES/code/output/ex26.res

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DeterministicTunedModel(
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model = KNNRidgeBlend(
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knn_model = KNNRegressor @ 1…65,
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ridge_model = RidgeRegressor @ 4…91,
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knn_model = KNNRegressor @ 4…17,
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ridge_model = RidgeRegressor @ 1…72,
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knn_weight = 0.3),
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tuning = Grid(
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goal = nothing,
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measure = rmsl(),
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weights = nothing,
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operation = MLJModelInterface.predict,
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range = MLJBase.NumericRange{MLJBase.Bounded,T,Symbol} where T[NumericRange @ 8…14, NumericRange @ 3…25, NumericRange @ 2…80],
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range = MLJBase.NumericRange{MLJBase.Bounded,T,Symbol} where T[NumericRange @ 4…51, NumericRange @ 4…66, NumericRange @ 2…80],
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train_best = true,
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repeats = 1,
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n = nothing,
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acceleration = ComputationalResources.CPU1{Nothing}(nothing),
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acceleration_resampling = ComputationalResources.CPU1{Nothing}(nothing),
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check_measure = true) @ 1…77
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check_measure = true) @ 8…56

‎__site/assets/end-to-end/AMES/code/output/ex4.res

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Machine{ConstantRegressor} @ 1…06
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Machine{ConstantRegressor} @ 8…18

‎__site/assets/end-to-end/AMES/code/output/ex8.res

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metric = Distances.Euclidean(0.0),
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leafsize = 10,
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reorder = true,
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weights = :uniform) @ 1…95
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weights = :uniform) @ 2…23

‎__site/assets/end-to-end/AMES/code/output/ex9.res

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Source{:target} @ 1…91
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Source{:target} @ 1…35

‎__site/assets/end-to-end/crabs-xgb/code/ex17.jl

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# This file was generated, do not modify it. # hide
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ŷ = predict_mode(mtm, rows=test)
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round(accuracy(ŷ, y[test]), sigdigits=3)
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round(accuracy(ŷ, y[test]), sigdigits=3)
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PyPlot.close_figs() # hide

‎__site/assets/end-to-end/crabs-xgb/code/ex7.jl

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figure(figsize=(8,6))
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plot(curve.parameter_values, curve.measurements)
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xlabel("Number of rounds", fontsize=14)
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ylabel("Cross entropy", fontsize=14)
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ylabel("HingeLoss", fontsize=14)
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xticks([10, 100, 200, 500], fontsize=12)
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yticks(1.46:0.005:1.475, fontsize=12)
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