cuml_example_02.py

# Import the libraries
import pandas as pd
import cudf
import cuml
from cuml.datasets import make_classification
from cuml.model_selection import train_test_split

# Generating a sample Pandas DataFrame
X, y = make_classification(n_samples=1000, n_features=4, n_classes=2, random_state=42)

# Splitting the data into training and testing sets
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

# Creating and fitting a Random Forest Classifier using cuML
rf_classifier = cuml.ensemble.RandomForestClassifier(n_estimators=100)
rf_classifier.fit(X_train, y_train)

# Predicting on the test set
y_pred = rf_classifier.predict(X_test)

# Displaying sample predictions
print("Sample predictions:")
print(y_pred[:10])