import dask_ml.datasets as dask_datasets
from dask_ml.linear_model import LogisticRegression
from dask_ml.model_selection import train_test_split

# Load a classification dataset using Dask
X, y = dask_datasets.make_classification(n_samples=100000, chunks=1000)

# Split the data into train and test sets
X_train, X_test, y_train, y_test = train_test_split(X, y)

# Train a logistic regression model in parallel
model = LogisticRegression()
model.fit(X_train, y_train)

# Predict on the test set
y_pred = model.predict(X_test).compute()