Which of the following forms of data mining assigns records to one of a predefined set of classes?

Question

BlackTom AI · Accepted Answer

The question asks about data mining methods that place records into one of a predefined set of classes, which points toward supervised learning tasks.
Option 1: Clustering. This is an unsupervised technique where similar records are grouped together without predefined labels or classes, so it does not assign records to predefined classes.
Option 2: Classification. This is the method that assigns each record to one of a fixed set of categories (classes) based on learned patterns from labeled training data, aligning exactly with the description in the question.
Option 3: Estimation. This term is vague in this context but generally refers to predicting a numerical value (regression-like) rather than assigning a class label, so it does not fit the idea of predefined classes.
Option 4: Affinity Grouping. This is typically associated with techniques like association rule mining (e.g., market basket analysis) to find relationships between items, not to classify records into predefined classes.

Which of the following forms of data mining assigns records to one of a predefined set of classes? Single choice

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