inc-search.py

from dask_ml.model_selection import RandomizedSearchCV
from dask_ml.wrappers import Incremental
from dask_ml.datasets import make_classification
from sklearn.linear_model import SGDClassifier
import numpy as np
from sklearn.model_selection import KFold

X, y = make_classification(chunks=20)

params = {'estimator__alpha': np.logspace(-3, 0)}
search = RandomizedSearchCV(Incremental(SGDClassifier()), params, cv=KFold(5))

search.fit(X, y, classes=[0, 1])

print(search.best_score_)
print(search.best_params_)