pascalabcnet/InstallerSamples/MachineLearning/08_Datasets/MoscowHousing/10_FeatureImportance1.pas

27 lines
577 B
ObjectPascal

uses MLABC;
begin
var ds := Datasets.MoscowHousing;
var df := ds.Data;
var features := ['rooms','area', 'kitchen_area', 'floor', 'floors_total', 'metro_minutes', 'renovation'];
var target := 'price';
var model := new RandomForestRegressor(seed := 42);
var pipe :=
DataPipeline.Build(
target,
features,
new LabelEncoder('renovation'),
model
);
pipe.Fit(df);
var imp := model.FeatureImportances;
Println('Feature importance:');
for var i := 0 to features.Length-1 do
Println(features[i]:15, ':', imp[i]:0:3);
end.