We are independent & ad-supported. We may earn a commission for purchases made through our links.
Advertiser Disclosure
Our website is an independent, advertising-supported platform. We provide our content free of charge to our readers, and to keep it that way, we rely on revenue generated through advertisements and affiliate partnerships. This means that when you click on certain links on our site and make a purchase, we may earn a commission. Learn more.
How We Make Money
We sustain our operations through affiliate commissions and advertising. If you click on an affiliate link and make a purchase, we may receive a commission from the merchant at no additional cost to you. We also display advertisements on our website, which help generate revenue to support our work and keep our content free for readers. Our editorial team operates independently of our advertising and affiliate partnerships to ensure that our content remains unbiased and focused on providing you with the best information and recommendations based on thorough research and honest evaluations. To remain transparent, we’ve provided a list of our current affiliate partners here.
Software

Our Promise to you

Founded in 2002, our company has been a trusted resource for readers seeking informative and engaging content. Our dedication to quality remains unwavering—and will never change. We follow a strict editorial policy, ensuring that our content is authored by highly qualified professionals and edited by subject matter experts. This guarantees that everything we publish is objective, accurate, and trustworthy.

Over the years, we've refined our approach to cover a wide range of topics, providing readers with reliable and practical advice to enhance their knowledge and skills. That's why millions of readers turn to us each year. Join us in celebrating the joy of learning, guided by standards you can trust.

What Is Biclustering?

By T.S. Adams
Updated: May 16, 2024
Views: 10,157
Share

Biclustering is a data mining technique which sorts information into a matrix by assigning the rows and columns of the matrix at the same time. At the core of this technique is efficiency, allowing the computer to sift through and sort a large amount of data in a shorter amount of time compared to single clustering methods. Biclustering is simply a general heading of one particular class of data mining techniques; there are many different algorithms which can fall under this category, including block clustering, the Plaid model, coupled two-way clustering, and interrelated two-way clustering.

To understanding the importance of biclustering, one must first understand the general concept of data mining. Data mining is taking a large pile of data — such as information dumped from a company's main database — and sorting through it to identify trends and other useful patterns. This type of analysis can be used to determine patterns which otherwise would not become evident through casual study, such as consumer purchasing trends and stock market fluctuations. Data mining can be conducted manually by a human analyst, or electronically using an type of data mining algorithm; that is where biclustering comes into play.

During the process of data mining, the computer conducting the analysis will attempt to sort related pieces of information together with one another. This process is known as "clustering." Clustering allows the computer to flex its artificial intelligence by recognizing when two or more pieces of information are related to one another, placing them together in a matrix. Normally, either the rows or the columns of the matrix are filled, but only one at a time.

Biclustering does away with this by limitation by enabling the computer to fill both the rows and the columns at the same time. This improves the efficiency of the clustering process, but can result in differently-arranged matrices depending on the particular algorithm being used. For example, a computer arranging things with constant matching values in rows versus one arranging things with constant matching values placed in columns will generate different looking matrices using the exact same values. There is no one "right" way to cluster the data; it all depends on the particular situation and preferences of the individual conducting the data mining.

Share
EasyTechJunkie is dedicated to providing accurate and trustworthy information. We carefully select reputable sources and employ a rigorous fact-checking process to maintain the highest standards. To learn more about our commitment to accuracy, read our editorial process.
Discussion Comments
Share
https://www.easytechjunkie.com/what-is-biclustering.htm
Copy this link
EasyTechJunkie, in your inbox

Our latest articles, guides, and more, delivered daily.

EasyTechJunkie, in your inbox

Our latest articles, guides, and more, delivered daily.