Airbnb competition on Kaggle
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README.md
airbnb-nonUS-travelers2.R
chk_j9.csv
descr.txt
highscore_jan18.R
lang-subsets.R
s1_a.csv
s1_b.csv
tree_airbnb_factorize.R

README.md

kaggle-airbnb

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:

Submission 3:

  1. highscore_jan18.R
    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.

  2. submit-chk2.csv
    .csv Excel submission file by formatting output of program highscore_jan18.R.
    This file gives a score of 0.83231


Submission 2:

  1. 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”.

  2. chk_j9.csv .csv Excel submission file by combining outputs of two programs:

    1. airbnb-nonUS-travelers2.R and
    2. s1_a.csv

This file gives a score of 0.80885


Submission 1:

  1. tree_airbnb_factorize.R ctree() to create predictive model for estimating destination for airbnb users.

  2. lang-subsets.R Predictive analysis for airbnb kaggle competition, to estimate which destination users want to travel, based on their language and gender.

  3. s1_a.csv Kaggle submission Excel (.csv) file combining output from two R programs:

    1. tree_airbnb_factorize.R and
    2. lang-subsets.R

(note: s1_b is a copy of the same file) This file gives a score of 0.79055