0

I am beginning to use Pybrain which good neural networks algorithms. If anybody is familiar with it already, is the package capable of doing multi-label classification as well? Multi-label is different from multi-class classification because an instance can have more than one class as their output/target.

ayush singhal
  • 1,879
  • 2
  • 18
  • 33

2 Answers2

1

Your question is a bit vague.

Yes

I believe I've understood you correctly, and yes PyBrain is capable of doing such a task. Neural networks in Pybrain are capable (through supervised learning1 ) of doing instance classification through multi-labeling the input values.

Just a tip:

Since you are performing a logical separation of the input instances I recommend using the sigmoid logistic function given that your input are in the range of [0, 1]. If your input range is the Real Numbers, the tanh has proven a lot faster on average2


Example outputs

    # The outputs are sqashed by the sigmoid( ) function

    0 1 1 0 # class one
    1 1 1 0 # class one
    0 0 1 0 # class two
    0 1 1 1 # class two
    0 0 1 0 # class three


1 I've not studied unsupervised learning, so I dare not state otherwise.
2 See this for a quick benchmark.
Keith Pinson
  • 7,835
  • 7
  • 61
  • 104
jorgenkg
  • 4,140
  • 1
  • 34
  • 48
1

Just in case, if it helps, Scikit-multilearn is another package which supports multi-label classification using deep learning libraries like theano, tensorflow, keras and scikit-neuralnetworks.

Nikhil
  • 1,054
  • 9
  • 9