taxi

Winning entry to the Kaggle taxi competition
git clone https://esimon.eu/repos/taxi.git
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dest_mlp_emb_only.py (715B)

      1 from blocks.initialization import IsotropicGaussian, Constant
      2 
      3 import data
      4 from model.mlp_emb import Model, Stream
      5 
      6 use_cuts_for_training = True
      7 
      8 dim_embeddings = [
      9     # ('origin_call', data.origin_call_train_size, 100),
     10     # ('origin_stand', data.stands_size, 100),
     11     # ('week_of_year', 52, 100),
     12     # ('day_of_week', 7, 100),
     13     ('qhour_of_day', 24 * 4, 10),
     14     ('day_type', 3, 1),
     15 ]
     16 
     17 dim_input = sum(x for (_, _, x) in dim_embeddings)
     18 dim_hidden = [10, 10]
     19 output_mode = "destination"
     20 dim_output = 2
     21 
     22 embed_weights_init = IsotropicGaussian(0.01)
     23 mlp_weights_init = IsotropicGaussian(0.01)
     24 mlp_biases_init = IsotropicGaussian(0.001)
     25 
     26 learning_rate = 0.001
     27 momentum = 0.9
     28 batch_size = 100
     29 
     30 max_splits = 100