diff options
Diffstat (limited to 'config/joint_simple_mlp_tgtcls_1_cswdtx.py')
| -rw-r--r-- | config/joint_simple_mlp_tgtcls_1_cswdtx.py | 54 |
1 files changed, 0 insertions, 54 deletions
diff --git a/config/joint_simple_mlp_tgtcls_1_cswdtx.py b/config/joint_simple_mlp_tgtcls_1_cswdtx.py deleted file mode 100644 index a66c98b..0000000 --- a/config/joint_simple_mlp_tgtcls_1_cswdtx.py +++ /dev/null @@ -1,54 +0,0 @@ -import os -import cPickle - -from blocks.initialization import IsotropicGaussian, Constant - -import data -from model.joint_simple_mlp_tgtcls import Model, Stream - - -n_begin_end_pts = 5 # how many points we consider at the beginning and end of the known trajectory - -with open(os.path.join(data.path, 'arrival-clusters.pkl')) as f: - dest_tgtcls = cPickle.load(f) - -# generate target classes for time prediction as a Fibonacci sequence -time_tgtcls = [1, 2] -for i in range(22): - time_tgtcls.append(time_tgtcls[-1] + time_tgtcls[-2]) - -dim_embeddings = [ - ('origin_call', data.origin_call_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), -] - -# Common network part -dim_input = n_begin_end_pts * 2 * 2 + sum(x for (_, _, x) in dim_embeddings) -dim_hidden = [500] - -# Destination prediction part -dim_hidden_dest = [] -dim_output_dest = len(dest_tgtcls) - -# Time prediction part -dim_hidden_time = [] -dim_output_time = len(time_tgtcls) - -# Cost ratio between distance cost and time cost -time_cost_factor = 4 - -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 = 200 - -valid_set = 'cuts/test_times_0' -max_splits = 100 |