taxi

Winning entry to the Kaggle taxi competition
git clone https://esimon.eu/repos/taxi.git
Log | Files | Refs | README

bidirectional_1.py (600B)


      1 from blocks.initialization import IsotropicGaussian, Constant
      2 
      3 import data
      4 from model.bidirectional_tgtcls import Model, Stream
      5 
      6 
      7 dim_embeddings = [
      8     ('origin_call', data.origin_call_train_size, 10),
      9     ('origin_stand', data.stands_size, 10),
     10     ('week_of_year', 52, 10),
     11     ('day_of_week', 7, 10),
     12     ('qhour_of_day', 24 * 4, 10),
     13     ('taxi_id', data.taxi_id_size, 10),
     14 ]
     15 
     16 hidden_state_dim = 100
     17 
     18 dim_hidden = [500, 500]
     19 
     20 embed_weights_init = IsotropicGaussian(0.01)
     21 weights_init = IsotropicGaussian(0.1) 
     22 biases_init = Constant(0.01)
     23 
     24 batch_size = 20
     25 batch_sort_size = 20
     26 
     27 max_splits = 100