AI Terms Dictionary

Definition

In statistical modeling and machine learning, a linear predictor function represents the weighted sum of input features plus a bias term. It serves as the core component in generalized linear models (GLMs) and linear regression, mapping input vectors to a real-valued score before being passed through a link function. This function assumes a linear relationship between predictors and the target variable, forming the basis for many interpretable algorithms used in classification and regression tasks.

Summary

A mathematical function that computes a linear combination of input variables to predict an outcome.

Key Concepts

• Weighted sum
• Bias term
• Generalized linear models
• Feature coefficients

Use Cases

• Linear regression analysis
• Logistic regression classification
• Support vector machines (kernel trick context)

Code Example

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import numpy as np
X = np.array([[1, 2], [3, 4]])
w = np.array([0.5, 1.0])
b = 0.1
prediction = np.dot(X, w) + b

Related Terms

• regression_coefficients
• bias_intercept
• feature_engineering
• generalized_linear_model