Classification

Classification is the process of assigning data items to predefined categories or classes.

Classification is used in various applications such as spam detection, image recognition, and medical diagnosis. It helps in organizing data into meaningful groups for better analysis and decision-making.

The process involves training a model on a labeled dataset where the categories are known. The model learns to identify patterns and relationships in the data that correspond to each category.

For example, in an email filtering system, Classification might be used to categorize emails as spam or not spam based on their content.

Classification can be either binary (two classes) or multi-class (more than two classes). Ordinal classification is a subtype of multi-class classification where the categories have a meaningful order but no numeric difference between them, such as rating levels from poor to excellent.

Common algorithms used for classification include Decision Trees, Support Vector Machines, and Neural Networks.

Understanding and implementing classification techniques is essential for building effective machine learning models that can make accurate predictions and decisions.