Overview

pyhnn3 - Heterogeneous Neuronal Networks 3

Dependencies

  • MLPY >= 2.2.0
  • SciPy >= 0.7.2
  • NumPy >= 1.3.0

Data Set Header

You have to add the following lines to the beginning of the data set file to can be used with pyhnn3.

  • Line 1: Type of problem, "cls" for classification problems, "rgs" for regression problems.
  • Line 2: Number of attributes.
  • Line 3: Character for missing values.

To define the type of each attribute you have to put:

  • "int" for integer attributes.
  • "real" for real attributes.
  • "set" following of the possible values for nominal attributes.
  • "ord" following of the possible values for ordinal attributes with "<" order.
  • "bin" for binary attributes.
  • "class" for class attributes.

For classification problems, class attributes have to be coded as 0-1 sequences.

Example:

Hepatitis data set:

cls
16
?
int
set 0 1
set 1 2 3 4
real
real
set 0 1
set 0 1 2
real
set 0 1
real
set 1 2 3
real
set 3 6 7
class
class
class

How to use

$ python pyhnn3.py -n {initial population} {dataset}