In data science, a classifier is a type of machine learning algorithm used to assign a class label to a data input. An example is an image recognition classifier to label an image (e.g., “car,” “truck,” or “person”). Classifier algorithms are trained using labeled data; in the image recognition example, for instance, the classifier receives training data that labels images. After sufficient training, the classifier then can receive unlabeled images as inputs and will output classification labels for each image.
Classifier algorithms employ sophisticated mathematical and statistical methods to generate predictions about the likelihood of a data input being classified in a given way. In the image recognition example, the classifier statistically predicts whether an image is likely to be a car, a truck, or a person, or some other classification that the classifier has been trained to identify.
Classification – i.e., assigning a data input with a specific class label – is a fundamental function of many enterprise AI applications, and classifiers are a core element in many of these applications. Classifiers are widely used for a range of common use cases, such as identifying if a customer belongs to a certain segment, identifying whether a financial transaction is fraudulent, or determining whether a piece of field equipment is in operable condition based on a photo or video footage.
Classification is a robust area of ongoing machine learning research and innovation. Significant academic and commercial effort has been invested in developing a diverse selection of classifier algorithms optimized for different types of classification problems. Numerous robust classifier methods have been developed and many are available through open source libraries, for example Python classifiers from Pypi.org.
The C3 AI® Suite not only provides a rich library of classifiers for use in building enterprise AI applications, but a complete set of capabilities to simplify and accelerate the use of classifiers in enterprise AI applications. The C3 AI Suite provides and supports an extensive library of machine learning algorithms for classification, such as tree-based models, logistic regression, and deep neural networks. The C3 AI Suite provides tools and capabilities enabling data scientists and developers to create their own custom classifiers.
Classifier algorithms are trained using labeled data as inputs. Training a classifier typically requires a significantly large set of labeled training data in order to achieve an acceptable level of precision. The C3 AI Suite provides extensive capabilities to simplify and accelerate classifier training and to test, tune, and validate classifier performance. Using C3 AI Suite’s powerful machine learning pipelines functionality, developers can rapidly and easily build sophisticated AI applications that employ a number of machine learning algorithms, including multiple classifiers, with far less code and complexity than other approaches.
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