taxi

Winning entry to the Kaggle taxi competition
git clone https://esimon.eu/repos/taxi.git
Log | Files | Refs | README

time_mlp_tgtcls.py (1034B)

      1 import numpy
      2 import theano
      3 from theano import tensor
      4 from blocks.bricks import application, Softmax
      5 
      6 import error
      7 from model.mlp import FFMLP, Stream
      8 
      9 
     10 class Model(FFMLP):
     11     def __init__(self, config, **kwargs):
     12         super(Model, self, output_layer=Softmax).__init__(config, **kwargs)
     13         self.classes = theano.shared(numpy.array(config.tgtcls, dtype=theano.config.floatX), name='classes')
     14         self.inputs.append('input_time')
     15 
     16     @application(outputs=['duration'])
     17     def predict(self, **kwargs):
     18         cls_probas = super(Model, self).predict(**kwargs)
     19         return kwargs['input_time'] + tensor.dot(cls_probas, self.classes)
     20 
     21     @predict.property('inputs')
     22     def predict_inputs(self):
     23         return self.inputs
     24 
     25     @application(outputs=['cost'])
     26     def cost(self, **kwargs):
     27         y_hat = self.predict(**kwargs)
     28         y = kwargs['travel_time']
     29         return error.rmsle(y_hat.flatten(), y.flatten())
     30 
     31     @cost.property('inputs')
     32     def cost_inputs(self):
     33         return self.inputs + ['travel_time']