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Trajan Neural Network
        After initially confirming the validity of using machine learning algorithms for predicting the invasive potential of weeds, we chose to continue with the Trajan neural network simulator for the following reasons:
    1. Trajan had the highest classification rate (approx. 70-74%).
    2. The ability to perform an exhaustive search for the best neural network.
    3. The ability to specify different types of variables (numeric, nominal, boolean).
Since we modified the set of input variables for the training set after the initial experiments, we specified another search for a set of neural networks with best performance. The Trajan neural network simulator returned a set of 10 networks (4 Radial Basis Function (RBF) and 6 Multilayer Perceptron (MLP) networks):
# Type Error Inputs Hidden Performance
01 RBF 0.4754761 17 39 0.6451613
02 RBF 0.4628958 17 36 0.6451613
03 MLP 0.4342738 13 2 0.7096774
04 MLP 0.3698627 2 3 0.7741935
05 MLP 0.3179705 2 3 0.8387097
06 RBF 0.4221949 3 11 0.9032258
07 RBF 0.4037507 2 11 0.8709677
08 MLP 0.3279516 3 3 0.8387097
09 MLP 0.2834223 4 3 0.9032258
10 MLP 0.2310261 5 2 0.9677419
We chose the best network (#10) based on training subset accuracy of 95.2 %, cross verification error of 23.1%, and test subset accuracy of 83.3% (see table below). This network also has the topology of 5 input nodes, 1 hidden layer with 2 nodes, and 1 output node (5-2-1):

The most effective 5 input attributes were determined to be:

  • Native range: Latitudinal range where native in Europe/Asia
  • Absolute range: Latitudinal range where native and exotic in Europe/Asia
  • Number of counties: Number of counties with the first record of species appearing within the 1951-2000 time period
  • Noxious elsewhere: How many states or provinces outside of ID and MT have declared the plant noxious
  • Lifeform: Forb, tree, shrub, grass-like or a spore-bearing vascular plant.
The network was trained with Back Propagation (50 epochs) and Conjugate Gradient Descent (91 epochs) algorithms. This network classified the training set instances as follows:

After selecting this best trained neural network, we ran an analysis of the set of 120 exotics (our prediction set) reported to have been introduced after 1950. This set also contains a group of 16 species that have already been declared as noxious. This fact is particularly useful, since it allows for further assessment of the accuracy of the selected neural network model. The list of 29 species predicted to have the potential to be noxious, along with a brief discussion, follows on the next page.



<< Initial Experiments Results >>