Lottery Purchase Prediction Model

Objective and Goal

  • Predict the lottery type that the user in the session will buy, using the discrete features from the user face image and user’s historical purchase data.

  • Recommend lottery types to users and improve the order conversion rate, in order to increase sales revenue.

Data Source

  • The feature from the user face image in the Session (from Baidu Face Recognition API):

    Beauty, Expression, Emotion, Face ID (optional, only for old users)

  • Other features from Session:

    Session Time (in 24 hours)

  • Use the session face id to get user id, and retrieve the historical order data of this user:

    City, Lottery Type, New/Old Users, Lottery Station Type (supermarket, restaurant), Total Purchase Days, Frequently Purchase Lottery Type

    If this is a new user and there is no user id, the feature from historical order data will be replaced by mean or mode.

Data Cleaning and Selected Features

Transform the continuous variables to one-hot encoding variables, and check whether they are strongly correlated with the dependent variable. There are 18 features in total after variable selection:

Feature Source
Beauty session face
Laugh session face
Neutral Emotion session face
Positive Emotion session face
Session Time session
Yichang user attribute
Enshi user attribute
Wuhan user attribute
Ten Times Good Luck historical order
Qilecai historical order
Shilitaohua historical order
Other Lottery Type historical order
Total Purchase Days historical order
New User historical order
Clubhouse historical order
Chess Room historical order
Supermarket historical order
Restaurant historical order

Model Structure

Concatenate all the feaures, and input to a 3-layers MLP in PyTorch. Then perform a multiclass classification task and predict the lottery type the user will buy in the session (Two-color Ball, Ten Times Good Luck, Welfare Lottery 3D, Other Lottery Type).

Prediction result using historical data

Accuracy metrics using the data from 07/2021:

Type Accuracy
Average Accuracy 0.913
No Buy 0.833
Ten Times Good Luck 0.814
Two-color Ball 0.961
Welfare Lottery 3D 0.822
Other Lottery Type 0.908

Model Call Method

python3 \
    --port=8827 \
    --debug=False \
    --host='' \
    --appname='buy_prediction' \


View Github