Fuzzy C Means - Learn Data Science with Travis

Fuzzy C-Means Clustering with Python

Towards Data Science

Fuzzy C-means clustering algorithm is an unsupervised learning method. Before learning the details, let me first decipher its fancy name. So, “fuzzy” here means “not sure”, which indicates that it’s…

What is Fuzzy Clustering

Towards AI

Fuzzy clustering aims to solve the problem of one-to-many clustering and is a technique that assigns a degree of membership to each data point for each cluster, rather than assigning it to a single cl...

Fuzzy Systems: Life between the 1’s and 0's

Towards Data Science

Fuzzy Systems is a branch of Computational Intelligence hoping to represent the uncertainty of a fuzzy, uncertain world. Fuzzy systems find their inspiration in the imprecision of human language…

FuzzyWuzzy — the Before and After

Towards Data Science

In the previous article, I introduced FuzzyWuzzy library which calculates a 0–100 matching score for a pair of strings. The different FuzzyWuzzy functions enable us to choose the one that would most…

Natural Language Processing for Fuzzy String Matching with Python

Towards Data Science

In computer science, fuzzy string matching is the technique of finding strings that match a pattern approximately (rather than exactly). In another word, fuzzy string matching is a type of search…

Fuzzy sets & Fuzzy C-Means Clustering Algorithm

Analytics Vidhya

All the classification algorithms that we studied in the past, most of them are based on soft-based computation. Soft based computation means as we are giving the prediction from algorithm that point…...

Type-2 Fuzzy Sets

Towards Data Science

In a previous post, we have seen how we use a fuzzy set of type-1 when we cannot determine the membership of an element as 0 or 1. We can extend this concept when the circumstances are so fuzzy that…

Comparing Python’s Top Tools for Fuzzy Matching: PyFuzzy, FuzzyWuzzy, RecordLinkage, and RapidFuzz

Python in Plain English

Fuzzy matching is a process of matching records in a dataset that have similar, but not necessarily identical data. This type of matching is especially useful when dealing with large datasets, as it…

Understanding a Use Case of Fuzzing in Go

Better Programming

Fuzzing in action Photo by Tim Hüfner on Unsplash “Fuzz testing is a novel way to discover security vulnerabilities or bugs in software applications.” The concept of fuzzing was introduced in 1988, w...

Fuzz-testing

Software Architecture with C plus plus

A subcategory of DAST tools, fuzz-testing checks the behavior of your application when confronted with invalid, unexpected, random, or maliciously formed data. Such checks can be especially useful whe...

Fuzzy matching at scale

Towards Data Science

Update December 2020: A faster, simpler way of fuzzy matching is now included at the end of this post with the full code to implement it on any dataset Data in the real world is messy. Dealing…

Fuzzy Buzzy: Sussing Out the “Fuzzy Logic” of Buzzwords in Data Science

Towards Data Science

Disclaimer: This post does not involve the actual Fuzzy Logic. The term was originally intended as just a pun, but I later realised that it also demonstrates how the improper use of buzzwords can be…