---
datasets:
- scikit-learn/iris
---

```python
import joblib

model = joblib.load("iris_svm.joblib")
import json

with open("config.json", "r") as f:
    config = json.load(f)

features = config["features"]
target = config["targets"][0]
target_mapping = config["target_mapping"]

import numpy as np

# example input data
input_data = np.array([
    [5.1, 3.5, 1.4, 0.2],
    [4.9, 3.0, 1.4, 0.2],
    [6.2, 3.4, 5.4, 2.3]
])

# make sure the input data has the correct shape
if input_data.shape[1] != len(features):
    raise ValueError(f"Input data must have {len(features)} features.")

predicted_classes = model.predict(input_data)
predicted_class_names = [list(target_mapping.keys())[list(target_mapping.values()).index(predicted_class)] for predicted_class in predicted_classes]

print("Predicted classes:", predicted_class_names)
```