32 lines
1.1 KiB
ObjectPascal
32 lines
1.1 KiB
ObjectPascal
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uses MLABC;
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begin
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var ds := Datasets.TitanicRu;
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var df := ds.Data.Drop(['Id', 'Имя']);
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var ageImputer := new Imputer(['Возраст']);
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df := ageImputer.FitTransform(df);
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var portImputer := new Imputer('Саутгемптон', ['ПортПосадки']);
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df := portImputer.FitTransform(df);
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var sexEncoder := new LabelEncoder('Пол');
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df := sexEncoder.FitTransform(df);
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var portEncoder := new LabelEncoder('ПортПосадки');
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df := portEncoder.FitTransform(df);
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var features := ['Класс', 'Пол', 'Возраст', 'БратьяИСупруги', 'РодителиИДети', 'ЦенаБилета', 'ПортПосадки'];
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var X := df.ToMatrix(features);
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var y := df.GetIntColumn('Выжил');
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var model := new RandomForestClassifier(nTrees := 100, maxDepth := 6, minSamplesLeaf := 3, minSamplesSplit := 6, seed := 42);
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model.Fit(X, y);
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var imp := model.FeatureImportances;
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Println('Важность признаков для RandomForestClassifier');
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for var i := 0 to features.Length - 1 do
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Println($'{features[i],-18}: {imp[i]:F3}');
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end.
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