ACtE09 · Chapter 9AI & Neural Networks🏛️ Past Licensure QuestionID: 6edbccb2
In machine learning, the paradigm of training a model using a dataset consisting of input features paired with verified target ground-truth labels is called:
In machine learning, the paradigm of training a model using a dataset consisting of input features paired with verified target ground-truth labels is called:
Multiple Choice Options
- A✓ Correct Option
Supervised learning
- B
Unsupervised learning
- C
Reinforcement learning
- D
Semi-supervised learning
Detailed Technical Solution & Explanation
Supervised Learning trains a mathematical model on a dataset containing input vectors paired with explicit ground-truth target outputs (), learning an optimal mapping function that minimizes prediction error (loss).
Option Analysis:
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Option A (Supervised learning): Correct; learns from labeled input-output training pairs.
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Option B (Unsupervised learning): Discovers patterns in unlabeled data without target outputs.
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Option C (Reinforcement learning): Learns via environmental reward and penalty signals.
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Option D (Semi-supervised learning): Combines small labeled sets with large unlabeled datasets.
Reference: Demo2 · Set 2NEC Licensure Syllabus