sklearn.utils
.murmurhash3_32#
- sklearn.utils.murmurhash3_32(key, seed=0, positive=False)#
Compute the 32bit murmurhash3 of key at seed.
The underlying implementation is MurmurHash3_x86_32 generating low latency 32bits hash suitable for implementing lookup tables, Bloom filters, count min sketch or feature hashing.
- Parameters:
- keynp.int32, bytes, unicode or ndarray of dtype=np.int32
The physical object to hash.
- seedint, default=0
Integer seed for the hashing algorithm.
- positivebool, default=False
- True: the results is casted to an unsigned int
from 0 to 2 ** 32 - 1
- False: the results is casted to a signed int
from -(2 ** 31) to 2 ** 31 - 1
Examples
>>> from sklearn.utils import murmurhash3_32 >>> murmurhash3_32(b"Hello World!", seed=42) 3565178