Ensembles

from fling import Stacker

s = Stacker("data.csv", target="label",
         base_models=["logistic", "random_forest", "gradient_boosting"],
         meta_model="logistic", task="classification")
s.train()

from fling import Voter

v = Voter("data.csv", target="label",
        models=["logistic", "random_forest", "knn"],
        voting="soft", task="classification")
v.train()

from fling import Booster

b = Booster("data.csv", target="label", n_estimators=100, task="classification")
b.train()

from fling import BaggedModel

bm = BaggedModel("data.csv", target="label",
              base_model="decision_tree", n_estimators=20, task="classification")
bm.train()