Spaces:
Sleeping
Sleeping
| import pandas as pd | |
| from benchmark_runner import BenchmarkRunner | |
| import sys | |
| import os | |
| sys.path.append(os.path.join(os.path.dirname(__file__), '..', '..')) | |
| from backend.core.orchestrator import Orchestrator | |
| # Load datasets | |
| datasets = { | |
| "titanic": (pd.read_csv(os.path.join(os.path.dirname(__file__), '..', '..', 'datasets', 'real_world', 'titanic.csv')), "Survived"), | |
| "credit_default": (pd.read_csv(os.path.join(os.path.dirname(__file__), '..', '..', 'datasets', 'real_world', 'credit_default.csv')), "default.payment.next.month"), | |
| "house_prices": (pd.read_csv(os.path.join(os.path.dirname(__file__), '..', '..', 'datasets', 'real_world', 'house_prices.csv')), "Price"), | |
| "telecom_churn": (pd.read_csv(os.path.join(os.path.dirname(__file__), '..', '..', 'datasets', 'real_world', 'telecom_churn.csv')), "Churn"), | |
| "news_classification": (pd.read_csv(os.path.join(os.path.dirname(__file__), '..', '..', 'datasets', 'real_world', 'news_classification.csv')), "label"), | |
| } | |
| orchestrator = Orchestrator() | |
| runner = BenchmarkRunner() | |
| results = runner.run(orchestrator, datasets) | |
| print("Benchmark Results:") | |
| for result in results: | |
| print(result) | |
| # Save results to file | |
| with open("experiments/benchmark_results.json", "w") as f: | |
| import json | |
| json.dump(results, f, indent=4) | |