from sklearn.metrics.pairwise import linear_kernel
sim_matrix = linear_kernel(tfidf_matrix, tfidf_matrix)
when I try to get dot product I am getting this errro
MemoryError Traceback (most recent call last)
<ipython-input-19-2c4d43d4a89e> in <module>
1 from sklearn.metrics.pairwise import linear_kernel
----> 2 sim_matrix = linear_kernel(tfidf_matrix, tfidf_matrix)
~\anaconda3\lib\site-packages\sklearn\metrics\pairwise.py in linear_kernel(X, Y, dense_output)
1002 """
1003 X, Y = check_pairwise_arrays(X, Y)
-> 1004 return safe_sparse_dot(X, Y.T, dense_output=dense_output)
1005
1006
~\anaconda3\lib\site-packages\sklearn\utils\validation.py in inner_f(args, kwargs)
70 FutureWarning)
71 kwargs.update({k: arg for k, arg in zip(sig.parameters, args)})
---> 72 return f(*kwargs)
73 return inner_f
74
~\anaconda3\lib\site-packages\sklearn\utils\extmath.py in safe_sparse_dot(a, b, dense_output)
151 ret = np.dot(a, b)
152 else:
--> 153 ret = a @ b
154
155 if (sparse.issparse(a) and sparse.issparse(b)
~\anaconda3\lib\site-packages\scipy\sparse\base.py in matmul(self, other)
558 raise ValueError("Scalar operands are not allowed, "
559 "use '*' instead")
--> 560 return self.mul(other)
561
562 def rmatmul(self, other):
~\anaconda3\lib\site-packages\scipy\sparse\base.py in mul(self, other)
478 if self.shape[1] != other.shape[0]:
479 raise ValueError('dimension mismatch')
--> 480 return self._mul_sparse_matrix(other)
481
482 # If it's a list or whatever, treat it like a matrix
~\anaconda3\lib\site-packages\scipy\sparse\compressed.py in _mul_sparse_matrix(self, other)
514
515 indptr = np.empty(major_axis + 1, dtype=idx_dtype)
--> 516 indices = np.empty(nnz, dtype=idx_dtype)
517 data = np.empty(nnz, dtype=upcast(self.dtype, other.dtype))
518
MemoryError: Unable to allocate 2.04 GiB for an array with shape (546860044,) and data type int32
