Categories: AI/ML Research

The Search for the Sweet Spot in a Linear Regression with Numeric Features

Consistent with the principle of Occam’s razor, starting simple often leads to the most profound insights, especially when piecing together a predictive model. In this post, using the Ames Housing Dataset, we will first pinpoint the key features that shine on their own. Then, step by step, we’ll layer these insights, observing how their combined […]

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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…

August 23, 2024

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"

Building a Logistic Regression Classifier in PyTorch

Logistic regression is a type of regression that predicts the probability of an event. It is used for classification problems and has many applications in the fields of machine learning, artificial intelligence, and data mining. The formula of logistic regression is to apply a sigmoid function to the output of…

March 29, 2023

In "AI/ML Research"

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