taxi

Winning entry to the Kaggle taxi competition
git clone https://esimon.eu/repos/taxi.git
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commit 62171aa41bc6216822ceaad696a31d79be5ebe0b
parent 0725db3a1a3716e1a51ce3ac6f88ed5e83eae89a
Author: √Čtienne Simon <esimon@esimon.eu>
Date:   Mon, 27 Jul 2015 13:46:39 -0400

alexandre mlp no tgtcls

Diffstat:
Aconfig/dest_mlp_1_cswdtx_alexandre.py | 35+++++++++++++++++++++++++++++++++++
1 file changed, 35 insertions(+), 0 deletions(-)

diff --git a/config/dest_mlp_1_cswdtx_alexandre.py b/config/dest_mlp_1_cswdtx_alexandre.py @@ -0,0 +1,35 @@ +import os +import cPickle + +from blocks.initialization import IsotropicGaussian, Constant +from blocks.algorithms import Momentum + +import data +from model.dest_mlp import Model, Stream + + +n_begin_end_pts = 5 # how many points we consider at the beginning and end of the known trajectory + +dim_embeddings = [ + ('origin_call', data.origin_call_train_size, 10), + ('origin_stand', data.stands_size, 10), + ('week_of_year', 52, 10), + ('day_of_week', 7, 10), + ('qhour_of_day', 24 * 4, 10), + ('day_type', 3, 10), + ('taxi_id', 448, 10), +] + +dim_input = n_begin_end_pts * 2 * 2 + sum(x for (_, _, x) in dim_embeddings) +dim_hidden = [500] +dim_output = 2 + +embed_weights_init = IsotropicGaussian(0.01) +mlp_weights_init = IsotropicGaussian(0.1) +mlp_biases_init = Constant(0.01) + +step_rule = Momentum(learning_rate=0.01, momentum=0.9) + +batch_size = 200 + +max_splits = 100