Implementing Bloom Filters in Python and Understanding its error probability: A Step-by-Step Guide

<h1>Probability of False Positive and Relation among i, m, k</h1> <p>Assumes a function that selects each array position with equal probability. Considering<code>&nbsp;m</code>&nbsp;is a number of bits in the array the probability of selecting a bit is 1/m. and the probability of not setting a bit is</p> <p>p = 1&ndash;1/m</p> <p>and there are&nbsp;<code>k</code>&nbsp;hash function so the probability now for&nbsp;<strong>not setting a bit</strong>&nbsp;by k hash function is</p> <p>p = (1&ndash;1/m)**k</p> <p>and if there are&nbsp;<code>i</code>&nbsp;strings it becomes</p> <p><a href="https://techtonics.medium.com/implementing-bloom-filters-in-python-and-understanding-its-error-probability-a-step-by-step-guide-13c6cb2e05b7"><strong>Website</strong></a></p>