Predicting Airbnb New User Bookings

download Predicting Airbnb New User Bookings

of 25

  • date post

    07-Feb-2017
  • Category

    Technology

  • view

    118
  • download

    1

Embed Size (px)

Transcript of Predicting Airbnb New User Bookings

Predicting New User BookingsAnaelia Ovalle, Michael Liston, Brent Rucker

Table of ContentsIntroduction to Project & GoalData Pre-ProcessingModelsResultsDiscussion

Data Sources

Libraries

GoalUsing a dataset of 15 basic features, predict where the user will make their first booking

Country Destination

12 countries14 predictors possible

Data Pre-Processing

Observe all distributionsIdentify NAs and handle NAVaried Training and TestingDate Feature ExtractionOne-hot encode categoricals10/14 predictors categoricalBinning

Age Feature Imputed by Mean

Modeling with Multi-Class Classification

16 ModelsDecision TreesRandom ForestsAdaBoostQDAKNNXGBoostSVMNeural Network

How Many Trees?

Sample Code with Tuning Parameters

Feature Importances

Results

Discussion

Best Accuracy: Random Forest

Best Accuracy != Best Model

Best Precision: Gradient Boosting

ChallengesAccess to more structured dataMore sophisticated imputation methodsEvaluate more modelsMotives of AirbnbTime

Business ApplicationsPrecision vs RecallUse RecallIncrease FNIncrease SpamNegative impact on ReputationUse PrecisionDecrease SpamMore bang for buckSmarter Decisions

Thank you