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authorAlex Auvolat <alex.auvolat@ens.fr>2015-05-07 13:16:23 -0400
committerAlex Auvolat <alex.auvolat@ens.fr>2015-05-07 13:16:23 -0400
commit1ffd1fc355f6fddcb6cd3d93c0df58513d064472 (patch)
tree8fc93f32c3f94644338093ac4a8a66d8d316d5a5 /config/time_simple_mlp_tgtcls_2_cswdtx.py
parent1ff071800fc876eb6f2c25fe0eb1f7dc64efe0be (diff)
downloadtaxi-1ffd1fc355f6fddcb6cd3d93c0df58513d064472.tar.gz
taxi-1ffd1fc355f6fddcb6cd3d93c0df58513d064472.zip
Add target class based model for time prediction (seems to work)
Diffstat (limited to 'config/time_simple_mlp_tgtcls_2_cswdtx.py')
-rw-r--r--config/time_simple_mlp_tgtcls_2_cswdtx.py41
1 files changed, 41 insertions, 0 deletions
diff --git a/config/time_simple_mlp_tgtcls_2_cswdtx.py b/config/time_simple_mlp_tgtcls_2_cswdtx.py
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+++ b/config/time_simple_mlp_tgtcls_2_cswdtx.py
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+import model.time_simple_mlp_tgtcls as model
+
+from blocks.initialization import IsotropicGaussian, Constant
+
+import data
+
+n_begin_end_pts = 5 # how many points we consider at the beginning and end of the known trajectory
+n_end_pts = 5
+
+n_valid = 1000
+
+# generate target classes as a Fibonacci sequence
+tgtcls = [1, 2]
+for i in range(22):
+ tgtcls.append(tgtcls[-1] + tgtcls[-2])
+
+dim_embeddings = [
+ ('origin_call', data.origin_call_size+1, 10),
+ ('origin_stand', data.stands_size+1, 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, 100]
+dim_output = len(tgtcls)
+
+embed_weights_init = IsotropicGaussian(0.001)
+mlp_weights_init = IsotropicGaussian(0.01)
+mlp_biases_init = Constant(0.001)
+
+exp_base = 1.5
+
+learning_rate = 0.0001
+momentum = 0.99
+batch_size = 32
+
+valid_set = 'cuts/test_times_0'