tensorrec_example.py

import numpy as np
import tensorrec

# Build the model with default parameters
model = tensorrec.TensorRec()

# Generate some dummy data
interactions, user_features, item_features = tensorrec.util.generate_dummy_data(
    num_users=100,
    num_items=150,
    interaction_density=.05
)

# Fit the model for 5 epochs
model.fit(interactions, user_features, item_features, epochs=5, verbose=True)

# Predict scores for all users and all items
predictions = model.predict(user_features=user_features,
                            item_features=item_features)

# Calculate and print the recall at 10
r_at_k = tensorrec.eval.recall_at_k(model, interactions,
                                    k=10,
                                    user_features=user_features,
                                    item_features=item_features)
print(np.mean(r_at_k))