HI guys, how do you get the predictions? I woud like to calculate those parameters but I can not If I do not get the predictions.
regards. El sábado, 30 de julio de 2016, 7:37:39 (UTC+2), Ivy Junior escribió: > > In theano, "for" can be subsititued by "scan", and it worked! > > true_pos, _ = theano.scan(fn = lambda nx, y, y_pred, mask: > (tensor.eq(y, nx)*tensor.eq(y_pred, nx)*mask).sum(), > outputs_info = None, > non_sequences = [y, y_pred, mask], > sequences = tensor.arange(n_labels)) > false_pos, _ = theano.scan(fn = lambda nx, y, y_pred, mask:\ > > (tensor.neq(y, nx)*tensor.eq(y_pred, nx)*mask).sum(),\ > outputs_info = None, > non_sequences = [y, y_pred, mask], > sequences = tensor.arange(n_labels)) > false_neg, _ = theano.scan(fn = lambda nx, y, y_pred, mask: > (tensor.eq(y, nx)*tensor.neq(y_pred, nx)*mask).sum(), > outputs_info = None, > non_sequences = [y, y_pred, mask], > sequences = tensor.arange(n_labels)) > > My task is sequence labeling, like multi_class classification, so, > r = ((true_pos+0.01) /( true_pos + false_pos+0.02)).mean() > p = ((true_pos+0.01) /(true_pos + false_neg+0.02)).mean() > f1 = 2*r*p/(r+p) > > 在 2015年5月12日星期二 UTC+8下午1:35:09，Mehdi写道： >> >> Hi, >> >> I adapted the code in this >> <https://github.com/Newmu/Theano-Tutorials/blob/master/3_net.py>page and >> I need to calculate the precision, accuracy, and recall of my model. I >> assume np.mean(np.argmax(teY, axis=1) == predict(teX)) calculates the >> accuracy of the model. Not sure how to calculate the recall and percision. >> Any help is appreciated. >> > -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
