Internet, Networking, & Security Around the Web 51 51 people found this article helpful The Use of Classification in Data Mining Classification techniques support data analysis and outcomes prediction by Mike Chapple Writer Former Lifewire writer Mike Chapple is an IT professional with more than 10 years' experience cybersecurity and extensive knowledge of SQL and database management. our editorial process Twitter Mike Chapple Updated on July 20, 2020 Tweet Share Email Around the Web Browsers Cloud Services Error Messages Family Tech Home Networking 5G Antivirus Around the Web Classification is a data-mining technique that assigns categories to a collection of data to aid in more accurate predictions and analysis. Classification is one of several methods intended to make the analysis of very large datasets effective. Why Classification? Very large databases are becoming the norm in today's world of big data. Imagine a database with terabytes of data—a terabyte is one trillion bytes of data. Facebook alone crunches 600 terabytes of new data every single day (as of 2014, the last time it reported these specs). The primary challenge of big data is how to make sense of it. And sheer volume is not the only problem: big data also tends to be diverse, unstructured and fast-changing. Consider audio and video data, social media posts, 3D data, or geospatial data. This kind of data is not easily categorized or organized. To meet this challenge, a range of automatic methods for extracting useful information has been developed, among them classification. Hero Images/Getty Images How Classification Works An analyst's goal is to create a set of classification rules that answer a question, make a decision, or predict behavior. To start, a set of training data is developed that contains a certain set of attributes as well as the likely outcome. The job of the classification algorithm is to discover how that set of attributes reaches its conclusion. Consider a credit-card company trying to determine which prospects should receive a credit card offer. The company's training data might include: Name Age Gender Annual Income Credit Card Offer John Doe 25 M $39,500 No Jane Doe 56 F $125,000 Yes Training Data The predictor columns Age, Gender, and Annual Income determine the value of the "predictor attribute" Credit Card Offer. In a training set, the predictor attribute is known. The classification algorithm then tries to determine how the value of the predictor attribute was reached: what relationships exist between the predictors and the decision? It will develop a set of prediction rules, usually an IF/THEN statement. Obviously, this is a simple example, and the algorithm would need a far larger data sampling than the two records shown here. Further, the prediction rules are likely to be far more complex, including sub-rules to capture attribute details. Next, the algorithm is given a "prediction set" of data to analyze, but this set lacks the prediction attribute (or decision): Name Age Gender Annual Income Credit Card Offer Jack Frost 42 M $88,000 Mary Murray 16 F $0 Predictor Data This predictor data helps estimate the accuracy of the prediction rules, and the rules are then tweaked until the developer considers the predictions effective and useful. Day to Day Examples of Classification Classification and other data-mining techniques are behind much of our day-to-day experience as consumers. Weather predictions use of classification techniques to report whether the day will be rainy, sunny, or cloudy. The medical profession analyzes health conditions to predict likely medical outcomes. A type of classification method, Naive Bayesian, uses conditional probability to categorize spam emails. Was this page helpful? Thanks for letting us know! Get the Latest Tech News Delivered Every Day Email Address Sign up There was an error. Please try again. You're in! Thanks for signing up. There was an error. Please try again. Thank you for signing up. Tell us why! Other Not enough details Hard to understand Submit More from Lifewire Defining the Regression Statistical Model What Is Quantum Computing? What Is a Neural Network? WD My Passport SSD Review Defining a Database Domain What Is Data Mining? What is End-to-End Encryption? What Exactly Is 'Big Data'? A Database Attribute Defines the Properties of a Table Kaspersky Total Security Review Cyclemeter GPS Bicycling App for the iPhone Mobile Technology: AI in Phones The 8 Best Weight Lifting Apps of 2021 The 10 Best Face Recognition Apps for Android in 2021 Entity-Relationship Diagram Definition What Is K-Means Clustering?