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authorAlex Auvolat <alex.auvolat@ens.fr>2015-05-04 17:13:08 -0400
committerAlex Auvolat <alex.auvolat@ens.fr>2015-05-04 17:13:08 -0400
commit5f42c01231ccec377196472b6f4682b6afeb878d (patch)
tree8e0212399a951a57738574084234e7c75b4fe590 /config/simple_mlp_tgtcls_0.py
parentc912ef9424be973b11b4c7b7dbb2d32a8f3a9ab9 (diff)
downloadtaxi-5f42c01231ccec377196472b6f4682b6afeb878d.tar.gz
taxi-5f42c01231ccec377196472b6f4682b6afeb878d.zip
Add model with predefined target classes
Diffstat (limited to 'config/simple_mlp_tgtcls_0.py')
-rw-r--r--config/simple_mlp_tgtcls_0.py25
1 files changed, 25 insertions, 0 deletions
diff --git a/config/simple_mlp_tgtcls_0.py b/config/simple_mlp_tgtcls_0.py
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+++ b/config/simple_mlp_tgtcls_0.py
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+import cPickle
+
+import data
+
+import model.simple_mlp_tgtcls as model
+
+n_dow = 7 # number of division for dayofweek/dayofmonth/hourofday
+n_dom = 31
+n_hour = 24
+
+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
+
+with open(data.DATA_PATH + "/arrival-clusters.pkl") as f: tgtcls = cPickle.load(f)
+
+dim_embed = 10
+dim_input = n_begin_end_pts * 2 * 2 + dim_embed + dim_embed
+dim_hidden = [200]
+dim_output = tgtcls.shape[0]
+
+learning_rate = 0.0001
+momentum = 0.99
+batch_size = 32