BloomFilter
Related Docs:
class BloomFilter
| package collection
The smallest BloomFilter that can provide the given false positive probability rate for the given number of elements. Asserts that the given probability can be satisfied using this filter.
A value between 0 and 1 which estimates the accuracy of the bloom filter.
A value between 0 and 1 which estimates the accuracy of the bloom filter. This estimate is precisely the inverse of the probability function for a bloom filter of a given capacity, width and number of hash functions. The probability function given by the following expression in LaTeX math syntax:
(1 - e^{-kn/m})^k where k is the number of hash functions,
n is the number of elements in the bloom filter and m is the
width.
It is important to remember that this is only an estimate of the accuracy. Likewise, it assumes perfectly ideal hash functions, thus it is somewhat more optimistic than the reality of the implementation.
Returns the optimal value of k for a bloom filter with the current properties (width and capacity).
Returns the optimal value of k for a bloom filter with the current properties (width and capacity). Useful in reducing false-positives on sets with a limited range in capacity.
Calculates the maximum number of buckets per element that this implementation can support.
Calculates the maximum number of buckets per element that this implementation can support. Crucially, it will lower the bucket count if necessary to meet BitSet's size restrictions.