taxi

Winning entry to the Kaggle taxi competition
git clone https://esimon.eu/repos/taxi.git
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dest_mlp_2_noembed.py (583B)

      1 from blocks.initialization import IsotropicGaussian, Constant
      2 
      3 import data
      4 from model.dest_mlp import Model, Stream
      5 
      6 
      7 n_begin_end_pts = 5     # how many points we consider at the beginning and end of the known trajectory
      8 
      9 dim_embeddings = []   # do not use embeddings
     10 
     11 dim_input = n_begin_end_pts * 2 * 2 + sum(x for (_, _, x) in dim_embeddings)
     12 dim_hidden = [200, 100]
     13 dim_output = 2
     14 
     15 embed_weights_init = IsotropicGaussian(0.001)
     16 mlp_weights_init = IsotropicGaussian(0.01)
     17 mlp_biases_init = Constant(0.001)
     18 
     19 learning_rate = 0.0001
     20 momentum = 0.99
     21 batch_size = 32
     22 
     23 max_splits = 100