Data Patterns in Ames Housing

, and
Posted on Jan 8, 2022

The skills I demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.

Ames Housing

There are many many parties who are greatly interested in accurate understanding of house prices for reasons both personal and financial. Therefore it is a subject of immense value to create good (or in some cases better) models for house prices, as well as deepening our conceptual understanding of the housing market in general.

We use various ML techniques to model the Ames, IA, housing price data, thereby considering different issues and tackling different problems associated with the same data set.

Neighborhood-based Demographic Visualization

We do the usual data cleaning and imputation that you would typically do for any data analysis project.

But in addition, we also do an exploratory analysis of Ames housing development. Specifically, we do a neighborhood and distance-based analysis to aggregate Ames houses and create a visualization of construction trends across over time and how they overlay neighborhoods and price.

House Values in different geographical areas

Data Patterns in Ames Housing

Data Patterns in Ames Housing

Linear Models

We use a generic multi-linear correlation model (implicitly without regularization) and compare that to a LASSO model with L1 penalties. Specifically, we compare the performance of each model on train/test sets to evaluate the possibility of overfitting.

The important features from the lasso regression is below

Data Patterns in Ames Housing

Data Patterns in Ames Housing

Tree Models

We also consider a generic Random Forest model and Gradient Boosting model along with a modified Random Forest model with a Term Structure adjustment. We evaluate the Random Forest vs. the Gradient Boosting model in terms of accuracy and feature importance, and we evaluate the Term Structure adjustment in terms of ensemble improvement to the Random Forest.

About Authors

john kosmicke

John is a quantitative technologist with experience in high frequency trading, recruiting, a master's degree from Iowa State and a bachelors's from Chicago.
View all posts by john kosmicke >

Cherie Wang

I worked in the Pharmaceutical industry and primarily focused on model building for oncology clinical trials. I am excited to learn more about machine learning as I pivot to a career in data science.
View all posts by Cherie Wang >

Related Articles

Leave a Comment

No comments found.

View Posts by Categories

Our Recent Popular Posts

View Posts by Tags

#python #trainwithnycdsa 2019 2020 Revenue 3-points agriculture air quality airbnb airline alcohol Alex Baransky algorithm alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus ames dataset ames housing dataset apartment rent API Application artist aws bank loans beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep boston safety Bundles cake recipe California Cancer Research capstone car price Career Career Day citibike classic cars classpass clustering Coding Course Demo Course Report covid 19 credit credit card crime frequency crops D3.js data data analysis Data Analyst data analytics data for tripadvisor reviews data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization database Deep Learning Demo Day Discount disney dplyr drug data e-commerce economy employee employee burnout employer networking environment feature engineering Finance Financial Data Science fitness studio Flask flight delay gbm Get Hired ggplot2 googleVis H20 Hadoop hallmark holiday movie happiness healthcare frauds higgs boson Hiring hiring partner events Hiring Partners hotels housing housing data housing predictions housing price hy-vee Income Industry Experts Injuries Instructor Blog Instructor Interview insurance italki Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter las vegas airport lasso regression Lead Data Scienctist Lead Data Scientist leaflet league linear regression Logistic Regression machine learning Maps market matplotlib Medical Research Meet the team meetup methal health miami beach movie music Napoli NBA netflix Networking neural network Neural networks New Courses NHL nlp NYC NYC Data Science nyc data science academy NYC Open Data nyc property NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time performance phoenix pollutants Portfolio Development precision measurement prediction Prework Programming public safety PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R Data Analysis R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn seafood type Selenium sentiment analysis sentiment classification Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau teachers team team performance TensorFlow Testimonial tf-idf Top Data Science Bootcamp Top manufacturing companies Transfers tweets twitter videos visualization wallstreet wallstreetbets web scraping Weekend Course What to expect whiskey whiskeyadvocate wildfire word cloud word2vec XGBoost yelp youtube trending ZORI