Hydra-Sklearn Blog - Code example 2

different_pipelines_for_different_models.py

from sklearn.decomposition import PCA
from sklearn.ensemble import RandomForestClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.tree import DecisionTreeClassifier

pipeline_lr = Pipeline(
    [
        ("imputer", SimpleImputer(strategy="constant", fill_value="-1")),
        ("VarianceThreshold", VarianceThreshold(threshold=0.1)),
        ("scalar1", StandardScaler()),
        ("pca1", PCA(n_components=2)),
        ("lr_classifier", LogisticRegression(random_state=0)),
    ]
)


pipeline_dt = Pipeline(
    [
        ("scalar2", StandardScaler()),
        ("VarianceThreshold", VarianceThreshold(threshold=0.1)),
        ("imputer", SimpleImputer(strategy="constant", fill_value="-1")),
        ("pca2", PCA(n_components=2)),
        ("dt_classifier", DecisionTreeClassifier()),
    ]
)

pipeline_randomforest = Pipeline(
    [
        ("scalar3", StandardScaler()),
        ("pca3", PCA(n_components=2)),
        ("rf_classifier", RandomForestClassifier()),
    ]
)