ValueError: setting an array element with a sequence. on DBSCAN, no missing dimensionality

Question

我在一个数据集上使用 DBSCAN.fit()，该数据集实际上是一个 pandas 带有矢量化词的单列，维度数相同，均为 30。它看起来像这样：

df['column']
2       [-0.003417029886667123, -0.0016105849274073794...
3       [-0.24330333298729837, 0.48110865717035506, 0....
4       [-0.0017016271879120766, 0.01266130386650884, ...
5       [0.002174357210089775, 0.004633570752676618, 0...
6       [0.008567001972125537, 0.0012244984475515731, ...

matrix = df['column'].as_matrix() 
#DBSCAN inplementation
db = DBSCAN(eps=0.06, min_samples=1)
db.fit(matrix)
clusters = db.labels_.tolist()

但是，在拟合数据后，我得到以下回溯：

----> 4 db.fit(matrix)
      5 clusters = db.labels_.tolist()

/opt/conda/lib/python3.6/site-packages/sklearn/cluster/dbscan_.py in fit(self, X, y, sample_weight)
    280 
    281         """
--> 282         X = check_array(X, accept_sparse='csr')
    283         clust = dbscan(X, sample_weight=sample_weight,
    284                        **self.get_params())

/opt/conda/lib/python3.6/site-packages/sklearn/utils/validation.py in check_array(array, accept_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator)
    431                                       force_all_finite)
    432     else:
--> 433         array = np.array(array, dtype=dtype, order=order, copy=copy)
    434 
    435         if ensure_2d:

ValueError: setting an array element with a sequence.

我了解到此错误与一个或多个数组与其他数组的长度不同有关。但是，就我而言，这似乎不是问题所在，请在下方留言：

set(np.array([m]).shape[0] for m in matrix)
>> {1}

set(np.array([m]).shape[1] for m in matrix)
>> {30}

如您所见，所有数组的长度都相同。因此可能是什么问题？

Answer 1

您将要素转换为数组的方式不是将其转换为数组，而是转换为列表数组，这就是您看到此错误的原因。

您可以将内部列表也转换为数组

ValueError: setting an array element with a sequence. on DBSCAN, no missing dimensionality

ValueError: setting an array element with a sequence. on DBSCAN, no missing dimensionality

python

pandas

dbscan

valueerror