Which of the following is considered a model family in machine learning?

Question

BlackTom AI · Accepted Answer

A model family is a collection of parameterized functional forms (hypothesis class) that define how inputs are mapped to outputs—for example linear models, decision trees, support vector machines, and neural networks. Deep learning (neural networks) is exactly such a family: architectures (MLP, CNN, RNN, transformers) specify a parametric function class governed by weights and activation functions.

Relevant concepts:
- Model family (hypothesis class): set of models sharing the same structure and parameterization.
- Learning paradigm/task (supervised, semi-supervised, reinforcement): describes the data and training framework, not the structural form of the model itself.
- Deep learning / neural networks: a parameterized function class that can approximate complex mappings by stacking layers of neurons.

Step-by-step reasoning:
1. Identify what each option represents:
   - Deep learning (neural networks): a structural class of models (layers, activations, weights) — a model family.
   - Supervised learning: a paradigm where models are trained with labeled input-output pairs.
   - Semi-supervised learning: a paradigm using both labeled and unlabeled data.
   - Reinforcement learning: a paradigm where agents learn via reward signals from interactions.
2. Test against the definition of model family: only the option that names a class of model architectures (neural networks) satisfies the definition.
3. Therefore deep learning is the model family; the others are training/feedback paradigms.

Why the correct answer is correct:
Neural networks specify how to combine parameters (weights, biases) and activations to form predictive functions. Different architectures produce different subfamilies, all under the “deep learning” umbrella—this matches the notion of a model family.

Why the other options are incorrect:
- Supervised, semi-supervised, and reinforcement learning describe learning settings or training methodologies, not specific model architectures or hypothesis classes.

Conclusion: Deep learning (neural networks) is the model family, which matches the provided correct answer.

Which of the following is considered a model family in machine learning?单项选择题

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