Airbnb competition on Kaggle Dataset is available from this link: https://www.kaggle.com/c/airbnb-recruiting-new-user-bookings/data
A description of all the files in this repository are given below:
We assume all users have two standard destination choices NDF&US (in that order). Based on some basic segmentation, according to age, gender and browser language, some users may have a third location preference too.
.csv Excel submission file by formatting output of program highscore_jan18.R.
This file gives a score of 0.83231
airbnb-nonUS-travelers2.R R program to design modified prediction tree model. A subset of the training set is used, without data from users who traveled to “US” or “NDF”.
chk_j9.csv .csv Excel submission file by combining outputs of two programs:
- airbnb-nonUS-travelers2.R and
This file gives a score of 0.80885
tree_airbnb_factorize.R ctree() to create predictive model for estimating destination for airbnb users.
lang-subsets.R Predictive analysis for airbnb kaggle competition, to estimate which destination users want to travel, based on their language and gender.
s1_a.csv Kaggle submission Excel (.csv) file combining output from two R programs:
- tree_airbnb_factorize.R and
(note: s1_b is a copy of the same file) This file gives a score of 0.79055