I can see the buggy code at lines 95-98. The problem is on line 95-96:

```python
    for k, v in params.items():
        if (v != init_params[k] and
                not (is_scalar_nan(init_params[k]) and is_scalar_nan(v))):
```

When `v` is a numpy array, `v != init_params[k]` returns an array of boolean values, and using that in an `if` statement causes the ValueError.

The fix changes `v != init_params[k]` to `repr(v) != repr(init_params[k])`.

Now I can generate the patch:

--- a/sklearn/utils/_pprint.py
+++ b/sklearn/utils/_pprint.py
@@ -92,7 +92,7 @@ def _changed_params(estimator):
     init_params = signature(init_func).parameters
     init_params = {name: param.default for name, param in init_params.items()}
     for k, v in params.items():
-        if (v != init_params[k] and
+        if (repr(v) != repr(init_params[k]) and
                 not (is_scalar_nan(init_params[k]) and is_scalar_nan(v))):
             filtered_params[k] = v
     return filtered_params