A data scientist creating categories and training an algorithm on large data sets is performing which learning technique?

The correct answer is A. Supervised. Supervised learning is defined by training a model on labeled data where the categories or output classes are predefined by humans. The data scientist explicitly creates the categories (labels) and then trains the algorithm to learn the mapping from inputs to those known…

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Question

Options

ASupervised
BReinforcement
CUnsupervised
DMachine learning (ML)

How the community answered

(29 responses)

A
86% (25)
B
7% (2)
C
3% (1)
D
3% (1)

Explanation

Supervised learning is defined by training a model on labeled data where the categories or output classes are predefined by humans. The data scientist explicitly creates the categories (labels) and then trains the algorithm to learn the mapping from inputs to those known outputs. Unsupervised learning (C) discovers hidden patterns or clusters in data without predefined labels. Reinforcement learning (B) uses reward and penalty signals from an environment, not pre-labeled categories. 'Machine learning' (D) is the broad field that encompasses all of these - it is not a specific technique and therefore not the correct specific answer.

Topics

#Supervised Learning#Machine Learning Techniques#Data Labeling#AI Training

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