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authorAdeB <adbrebs@gmail.com>2015-06-21 17:00:25 -0400
committerAdeB <adbrebs@gmail.com>2015-06-21 17:00:25 -0400
commit0fd3b1497ffa1bb625bf593c845e28901bc640b7 (patch)
treef03e58cbf9603d0bb3c32060e54d9756aa018048 /config
parent4cfba3efb678bc83c9528d603244310fec66c0c0 (diff)
downloadtaxi-0fd3b1497ffa1bb625bf593c845e28901bc640b7.tar.gz
taxi-0fd3b1497ffa1bb625bf593c845e28901bc640b7.zip
Model with only embeddings.
Diffstat (limited to 'config')
-rw-r--r--config/dest_simple_mlp_emb_only.py31
1 files changed, 31 insertions, 0 deletions
diff --git a/config/dest_simple_mlp_emb_only.py b/config/dest_simple_mlp_emb_only.py
new file mode 100644
index 0000000..e5c91b8
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+++ b/config/dest_simple_mlp_emb_only.py
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+from blocks.initialization import IsotropicGaussian, Constant
+
+import data
+from model.mlp_emb import Model, Stream
+
+use_cuts_for_training = True
+
+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),
+]
+
+dim_input = sum(x for (_, _, x) in dim_embeddings)
+dim_hidden = [200, 100]
+output_mode = "destination"
+dim_output = 2
+
+embed_weights_init = IsotropicGaussian(0.001)
+mlp_weights_init = IsotropicGaussian(0.01)
+mlp_biases_init = Constant(0.001)
+
+learning_rate = 0.0001
+momentum = 0.99
+batch_size = 32
+
+valid_set = 'cuts/test_times_0'
+max_splits = 100