from sklearn.pipeline import Pipeline
from sklearn.ensemble import RandomForestClassifier


def main(args):
    df = pd.load(args.df)

    rfc_seed = int(time.time() * 1000)
    estimators = [('reduce_dim', KernelPCA(kernel='linear')),
                  ('rfc', RandomForestClassifier(32, random_state=rfc_seed))]

    clf = Pipeline(estimators)