4819
1
weka.MultilayerPerceptron
6
Weka_3.9.0_12449
Weka implementation of MultilayerPerceptron
2016-10-06T19:19:18
English
Weka_3.9.0
-do-not-check-capabilities
flag
If set, classifier capabilities are not checked before classifier is built
(use with caution).
A
flag
Autocreation of the network connections will NOT be done.
(This will be ignored if -G is NOT set)
B
flag
A NominalToBinary filter will NOT automatically be used.
(Set this to not use a NominalToBinary filter).
C
flag
Normalizing a numeric class will NOT be done.
(Set this to not normalize the class if it's numeric).
D
flag
Learning rate decay will occur.
(Set this to cause the learning rate to decay).
E
option
20
The consequetive number of errors allowed for validation
testing before the netwrok terminates.
(Value should be > 0, Default = 20).
G
flag
GUI will be opened.
(Use this to bring up a GUI).
H
option
a
The hidden layers to be created for the network.
(Value should be a list of comma separated Natural
numbers or the letters 'a' = (attribs + classes) / 2,
'i' = attribs, 'o' = classes, 't' = attribs .+ classes)
for wildcard values, Default = a).
I
flag
Normalizing the attributes will NOT be done.
(Set this to not normalize the attributes).
L
option
0.3
Learning Rate for the backpropagation algorithm.
(Value should be between 0 - 1, Default = 0.3).
M
option
0.2
Momentum Rate for the backpropagation algorithm.
(Value should be between 0 - 1, Default = 0.2).
N
option
500
Number of epochs to train through.
(Default = 500).
R
flag
Reseting the network will NOT be allowed.
(Set this to not allow the network to reset).
S
option
0
The value used to seed the random number generator
(Value should be >= 0 and and a long, Default = 0).
V
option
0
Percentage size of validation set to use to terminate
training (if this is non zero it can pre-empt num of epochs.
(Value should be between 0 - 100, Default = 0).
batch-size
option
The desired batch size for batch prediction (default 100).
num-decimal-places
option
The number of decimal places for the output of numbers in the model (default 2).
output-debug-info
flag
If set, classifier is run in debug mode and
may output additional info to the console