Linear and Nonlinear Models for Real Estate Data
This repository contains data analyses, linear and nonlinear modelings, machine learning codes for different real estate datasets. Folders include the followings:
Ames Housing: Code is about reading and plotting the Ames Housing (xls format) data.
Ankara Cevizlidere Real Estate Sales: The xlsx files of the training, the test and area&price list of all data are given. In "cevizlidereModeling.R" file there are several modeling algorithms like linear regression, MARS, random forest, neural network, SVM, decision tree,
Boston Housing: We compare the rmse values of NN and linear regression of the Boston Housing data.
Housing Data ML: Predictions and classifications are calculated by several algorithms such as linear regression, logistic regression, least square regression, stepwise regression, k-nearest neighbor, k-means clustering, decision tree, AdaBoost, neural network, naive bayes and randon forest for Housing Dataset.
San Francisco Home Sales: In this folder there is a code to analyze and visualize the San Francisco Home Sales data.