00:00

Predicting House Prices in Ames, Iowa: A Comprehensive Analysis

In this Kaggle project, Anadil Mohammad, Mine Tuna, and Sümeyye Çangal explore predicting house sale prices in Ames, Iowa using a dataset with 79 predictor variables. They employ data cleaning techniques like handling missing values and then build baseline models with Decision Trees, Bagging, Random Forest, and Boosting. The team achieves promising results, ranking in the top 62% of participating teams, showcasing their understanding of model selection and evaluation.

silvent
Télécharger la présentation

Predicting House Prices in Ames, Iowa: A Comprehensive Analysis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

More Related