cataloteca.LevenshteinDistance 1.0.0

Cataloteca Algorithms

Library with machine learning algorithms from the 'cataloteca' project.

Levenshtein Distance

Algorithm used to calculate the distance and similarity between two strings.

How to use Levenshtein Distance Algorithm?

• Use Leveshtein project

	using cataloteca.algorithms.LevenshteinDistance;

• Define your reference, ie the string you want to compare with your data.

	string reference = "Example";

• Define your targets, ie the data you want to compare with the reference.

	List<string> exampleList = new List<string>(new string[] {
        "example 1",
        "example 2",
        "example 3"
    });

• Use the method to calculate distance and similarity. By default the method returns the distance and similarity values, but you may not return one of the metrics

	// Method that calculates string distance and similarity
    var bothCalc = new LevenshteinInput(reference, exampleList);
    var data = bothCalc.CallLevenstheinCalc(similarity:true, distance:true);

	// Console Response Sample

	// example
	// -------------------
	// example 1
	// Distance: 2,00 | Similarity: 77,78%

	// example 2
	// Distance: 2,00 | Similarity: 77,78%

	// example 3
	// Distance: 2,00 | Similarity: 77,78%

• Use the method to calculate similarity only

	// Method that calculates similarity only
		var similarityCalc = new LevenshteinInput(reference, exampleList);
		var data = similarityCalc.CallLevenstheinCalc(similarity:true, distance:false);


	// Console Response Sample

	// example
	// -------------------
	// example 1
	// Similarity: 77,78%

	// example 2
	// Similarity: 77,78%

	// example 3
	// Similarity: 77,78%

• Use the method to calculate distance only

	// Method that calculates only the distance
	var distanceCalc = new LevenshteinInput(reference, exampleList);
	var data = distanceCalc.CallLevenstheinCalc(similarity:false, distance:true);

	// Console Response Sample

	// example
	// -------------------
	// example 1
	// Distance: 2,00

	// example 2
	// Distance: 2,00

	// example 3
	// Distance: 2,00

Author: Lucas Alves Siqueira