bias update

[DimitriF]

A few changes:

• the option use_bias in trainr trigger the use of a bias for network calculation
• during the network crossing, I went step by step: weight multiplication, eventually bias addition, unit activation (last one is the sigmoid/logistic/stuff)
• if use_bias == T, a new object in the output list is added: bias_synapse
• in predictr, if bias_synapse in the list, the bias is added during network crossing

I didn't care about efficiency and calculate the bias anyway, I just take them into account or not during network crossing, I don't think there is a bottleneck here.

the RNG changed because of bias generation so I add a seed in the test_rnn.R and change the result (I needed it to check that the use_bias = F wasn't messing around compare to the last version)

[coveralls]

Coverage decreased (-1.2%) to 87.047% when pulling e7ffc91 on DimitriF:master into fd06501 on bquast:sigmoid.

[bquast]

perfect, again i'm going to have read this in more detail later, but the fact that it passes the test should say enough.

at some point in the future I will add some more tests just to be sure