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export_json.py

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+"""Export the trained Random Forest to model.json so a browser can run it (no server needed)."""
+import json
+import joblib
+
+bundle = joblib.load("model.joblib")
+model, classes = bundle["model"], bundle["classes"]
+
+trees = []
+for est in model.estimators_:
+    t = est.tree_
+    values = t.value[:, 0, :]
+    probs = (values / values.sum(axis=1, keepdims=True)).round(6).tolist()
+    trees.append({
+        "left": t.children_left.tolist(),
+        "right": t.children_right.tolist(),
+        "feature": t.feature.tolist(),
+        "threshold": [float(x) for x in t.threshold],
+        "probs": probs,
+    })
+
+with open("model.json", "w") as f:
+    json.dump({"classes": classes, "trees": trees}, f, separators=(",", ":"))
+print(f"Saved model.json with {len(trees)} trees")

model.json

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