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| import requests | |
| with open("mushrooms.csv", "rb") as csv: | |
| data = csv.read() | |
| # class,cap-shape,cap-surface,cap-color,bruises,odor,gill-attachment,gill-spacing,gill-size,gill-color,stalk-shape,stalk-root,stalk-surface-above-ring,stalk-surface-below-ring,stalk-color-above-ring,stalk-color-below-ring,veil-type,veil-color,ring-number,ring-type,spore-print-color,population,habitat | |
| ARGS = { | |
| "epochs": 1_000, | |
| "hidden_size": 8, | |
| "learning_rate": 0.0001, | |
| "test_size": 0.1, | |
| "activation": "relu", | |
| "features": [ | |
| "cap-shape", | |
| "cap-surface", | |
| "cap-color", | |
| "bruises", | |
| "odor", | |
| "gill-attachment", | |
| "gill-spacing", | |
| "gill-size", | |
| "gill-color", | |
| ], | |
| "target": "class", | |
| "data": data.decode("utf-8"), | |
| } | |
| if __name__ == "__main__": | |
| r = requests.post( | |
| "http://127.0.0.1:5000/neural-network", | |
| json=ARGS, # Send the data as a JSON object | |
| ) | |
| print(r.text) | |