From 54613c1f9cf510ca7a71d6619418f2247515aec6 Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Tue, 5 May 2015 14:15:21 -0400 Subject: Add models for time predictioAdd models for time prediction --- config/simple_mlp_tgtcls_1_cswdt.py | 29 ----------------------------- 1 file changed, 29 deletions(-) delete mode 100644 config/simple_mlp_tgtcls_1_cswdt.py (limited to 'config/simple_mlp_tgtcls_1_cswdt.py') diff --git a/config/simple_mlp_tgtcls_1_cswdt.py b/config/simple_mlp_tgtcls_1_cswdt.py deleted file mode 100644 index 45bd39e..0000000 --- a/config/simple_mlp_tgtcls_1_cswdt.py +++ /dev/null @@ -1,29 +0,0 @@ -import cPickle - -import data - -import model.simple_mlp_tgtcls as model - -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_embeddings = [ - ('origin_call', data.n_train_clients+1, 10), - ('origin_stand', data.n_stands+1, 10), - ('week_of_year', 52, 10), - ('day_of_week', 7, 10), - ('qhour_of_day', 24 * 4, 10), - ('day_type', 3, 10), -] - -dim_input = n_begin_end_pts * 2 * 2 + sum(x for (_, _, x) in dim_embeddings) -dim_hidden = [500] -dim_output = tgtcls.shape[0] - -learning_rate = 0.0001 -momentum = 0.99 -batch_size = 32 -- cgit v1.2.3