taxi

Winning entry to the Kaggle taxi competition
git clone https://esimon.eu/repos/taxi.git
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bidirectional_tgtcls_1.py (719B)

      1 import os
      2 import cPickle
      3 
      4 from blocks.initialization import IsotropicGaussian, Constant
      5 
      6 import data
      7 from model.bidirectional_tgtcls import Model, Stream
      8 
      9 
     10 with open(os.path.join(data.path, 'arrival-clusters.pkl')) as f: tgtcls = cPickle.load(f)
     11 
     12 dim_embeddings = [
     13     ('origin_call', data.origin_call_train_size, 10),
     14     ('origin_stand', data.stands_size, 10),
     15     ('week_of_year', 52, 10),
     16     ('day_of_week', 7, 10),
     17     ('qhour_of_day', 24 * 4, 10),
     18     ('taxi_id', data.taxi_id_size, 10),
     19 ]
     20 
     21 hidden_state_dim = 100
     22 
     23 dim_hidden = [500, 500]
     24 
     25 embed_weights_init = IsotropicGaussian(0.01)
     26 weights_init = IsotropicGaussian(0.1) 
     27 biases_init = Constant(0.01)
     28 
     29 batch_size = 100
     30 batch_sort_size = 20
     31 
     32 max_splits = 100
     33