Classification is one of two main types of supervised learning techniques (regression the other). Classification models predict a class label, such as whether a customer will return or not, whether a certain transaction represents fraud or not, or whether a certain image is a car or not. Classification approaches are useful for business problems that have large amounts of historical data, including labels, that specify if something is in one group or another. In unsupervised learning, clustering algorithms that group data in meaningful ways are a type of classification technique.
Classification is a machine learning technique that can effectively solve many business problems to deliver high value. An example of a classification task is predicting when an equipment or a machine is likely to fail. This predictive maintenance task is a common problem faced by manufacturing and operations-focused companies. Predictive maintenance can help avoid failure events that may be expensive or potentially dangerous. Another high-value use case for ML-based classification methods is the detection of fraud, money laundering, and other financial crimes.
The C3 AI Suite and C3 AI Applications enable organizations to apply pre-built classification models for many use cases and business problems, or to easily develop their own custom classification models to address specific requirements. Pre-built applications employing classification models include, for example, C3 AI Predictive Maintenance (available for a broad range of industries, including oil and gas, aerospace, manufacturing, petrochemicals, and more); C3 AI Fraud Detection; and C3 AI Anti-Money Laundering.
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