Supervised

term_id: supervised

Category: training_techniques

Definition

Supervised learning involves feeding an algorithm with data that includes both inputs and correct answers (labels). The model learns to map inputs to outputs by minimizing prediction errors. This technique is foundational for classification and regression tasks, requiring high-quality labeled datasets for effective training.

Summary

A machine learning paradigm where models are trained on labeled input-output pairs.

Key Concepts

  • Labeled data
  • Mapping
  • Loss minimization

Use Cases

  • Image classification
  • Spam detection
  • Price prediction

Code Example

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from sklearn.linear_model import LinearRegression
model = LinearRegression()
model.fit(X_train, y_train)

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