Categories: AI/ML Research

Interpreting Coefficients in Linear Regression Models

Linear regression models are foundational in machine learning. Merely fitting a straight line and reading the coefficient tells a lot. But how do we extract and interpret the coefficients from these models to understand their impact on predicted outcomes? This post will demonstrate how one can interpret coefficients by exploring various scenarios. We’ll delve into […]

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From Linear Regression to XGBoost: A Side-by-Side Performance Comparison

Regression is undoubtedly one of the most mainstream tasks machine learning models can address.

July 19, 2025

In "AI/ML Research"

Capturing Curves: Advanced Modeling with Polynomial Regression

When we analyze relationships between variables in machine learning, we often find that a straight line doesn’t tell the whole story. That’s where polynomial transformations come in, adding layers to our regression models without complicating the calculation process. By transforming our features into their polynomial counterparts—squares, cubes, and other higher-degree…

August 27, 2024

In "AI/ML Research"

Tips for Tuning Hyperparameters in Machine Learning Models

If you’re familiar with machine learning, you know that the training process allows the model to learn the optimal values for the parameters—or model coefficients—that characterize it. But machine learning models also have a set of hyperparameters whose values you should specify when training the model. So how do you…

August 7, 2024

In "AI/ML Research"

AI Generated Robotic Content