O código que eu fiz é:
misterio1 = [1,1.1]
misterio2 = [1,1,0]
misterio3 = [0,1,1]
testes = [misterio1, misterio2, misterio3]
model.predict (testes)
No entanto, retorna com o seguinte erro:
/usr/local/lib/python3.10/dist-packages/sklearn/utils/_array_api.py:185: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.
array = numpy.asarray(array, order=order, dtype=dtype)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-24-7b554ab05257> in <cell line: 6>()
4
5 testes = [misterio1, misterio2, misterio3]
----> 6 model.predict (testes)
3 frames
/usr/local/lib/python3.10/dist-packages/sklearn/utils/validation.py in check_array(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator, input_name)
900 # If input is 1D raise error
901 if array.ndim == 1:
--> 902 raise ValueError(
903 "Expected 2D array, got 1D array instead:\narray={}.\n"
904 "Reshape your data either using array.reshape(-1, 1) if "
ValueError: Expected 2D array, got 1D array instead:
array=[list([1, 1.1]) list([1, 1, 0]) list([0, 1, 1])].
Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.
Poderia me ajudar a solucionar, por favor.
