Categories: AI/ML Research

The Strategic Use of Sequential Feature Selector for Housing Price Predictions

To understand housing prices better, simplicity and clarity in our models are key. Our aim with this post is to demonstrate how straightforward yet powerful techniques in feature selection and engineering can lead to creating an effective, simple linear regression model. Working with the Ames dataset, we use a Sequential Feature Selector (SFS) to identify […]

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Feature Relationships 101: Lessons from the Ames Housing Data

In the realm of real estate, understanding the intricacies of property features and their impact on sale prices is paramount. In this exploration, we’ll dive deep into the Ames Housing dataset, shedding light on the relationships between various features and their correlation with the sale price. Harnessing the power of…

February 5, 2024

In "AI/ML Research"

The Concise Guide to Feature Engineering for Better Model Performance

Feature engineering helps make models work better. It involves selecting and modifying data to improve predictions. This article explains feature engineering and how to use it to get better results. What is Feature Engineering? Raw data is often messy and not ready for predictions. Features are important details in your…

September 19, 2024

In "AI/ML Research"

From Single Trees to Forests: Enhancing Real Estate Predictions with Ensembles

This post dives into the application of tree-based models, particularly focusing on decision trees, bagging, and random forests within the Ames Housing dataset. It begins by emphasizing the critical role of preprocessing, a fundamental step that ensures our data is optimally configured for the requirements of these models. The path…

September 24, 2024

In "AI/ML Research"

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