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Test Algorithm has 24 facts recorded in Dontopedia across 4 references, with 5 live disagreements.
Mostly:has parameter(5), returns(3), computes(3)
computescalculateshasSteprdf:typeperformsconvertscalledTwicedescriptionIncomputesMetricOther subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. “X motherOf this subject” — and answer questions the forward facts can't. Grouped by predicate.
describesDescribes(2)ex:explanationex:explanationSectioncalledAsArgumentCalled As Argument(1)ex:feedback_algorithmcallsCalls(1)ex:main_scriptcallsFunctionCalls Function(1)ex:accuracy_calculationcomputed_byComputed by(1)ex:accuracycomputedByComputed by(1)ex:accuracycontainsFunctionContains Function(1)ex:codeSnippetisParameterOfIs Parameter of(1)ex:interactionsused_byUsed by(1)ex:feedback_loop_algorithmTimeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.
doc:beam/41b29f03-8784-49da-b656-9a1b5c8d5506# Test the model true_ratings = [interaction[2] for interaction in test_interactions] predicted_ratings = [model.predict(user_id, item_id).est for user_id, item_id, _, _ in test_interactions] # Calculate accuracy ac…
doc:beam/755a2410-8559-42ef-a748-3e6658f03631# Load the test interactions interactions = np.load("interactions.npy", allow_pickle=True) # Test the algorithm def test_algorithm(algorithm, interactions): true_ratings = [interaction['rating'] for interaction in interactions] pre…
doc:beam/f6d6e5e8-2e81-4b5b-8ad1-a93a9616694creturn 1 - accuracy # Convert RMSE to accuracy-like metric # Load the test interactions interactions = np.load("interactions.npy") # Define the reader and load the dataset reader = Reader(rating_scale=(1, 5)) # Adjust the rating sca…
doc:beam/1da05a31-8d6c-42fb-be75-de09a6b68622self.partial_fit([(user_id, item_id, rating)]) # Monkey-patch the update method to the SVD class SVD.update = update # Re-test the algorithm with relevance scores accuracy_with_relevance = test_algorithm(feedback_loop_algorithm, i…
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