#BigData Hamming Distance | Big Data Analytics | Module 05 Finding Similar Items and Clustering | MU
Channel: Tech Educators
Date: 19/12/2020

In this video you will learn, What is hamming distance? How to calculate the Hamming Distance?  | hamming distance in machine learning | Hamming distance in Big Data Analytics | 
An effective distance metric improves the performance of our machine learning model, whether that’s for classification tasks or clustering.
Hamming Distance measures the similarity between two strings of the same length. The Hamming Distance between two strings of the same length is the number of positions at which the corresponding characters are different.

The Hamming distance between two strings of equal length is the number of positions at which the corresponding symbols are different. In other words, it measures the minimum number of substitutions required to change one string into the other, or the minimum number of errors that could have transformed one string into the other. 
In a more general context, the Hamming distance is one of several string metrics for measuring the edit distance between two sequences. 
A major application is in coding theory, more specifically to block codes, in which the equal-length strings are vectors over a finite field.
OR
“Hamming distance is a metric for comparing two binary data strings. While comparing two binary strings of equal length, Hamming distance is the number of bit positions in which the two bits are different.”
The Hamming distance between two strings, a and b is denoted as d(a,b).
It is used for error detection or error correction when data is transmitted over computer networks. It is also used in coding theory for comparing equal length data words.
Calculation of Hamming Distance
In order to calculate the Hamming distance between two strings, and , we perform their XOR operation, (a⊕ b), and then count the total number of 1s in the resultant string.
Example 
Suppose there are two strings 1101 1001 and 1001 1101.
11011001 ⊕ 10011101 = 01000100. Since, this contains two 1s, the Hamming distance, d(11011001, 10011101) = 2.

Hamming distance only works when we have strings or arrays of the same length.

🙏🙏🙏🙏🙏🙏🙏🙏
YOU JUST NEED TO DO 
3 THINGS to support my channel
LIKE
SHARE 
&
SUBSCRIBE 
TO MY YOUTUBE CHANNEL
🙏🙏🙏🙏🙏🙏🙏🙏

Keep Smiling and Keep Learning......