599
2
weka.MultiBoostAB_MultilayerPerceptron
2
Weka_3.7.12-SNAPSHOT_8109
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
2014-10-07T16:38:14
English
Weka_3.7.12-SNAPSHOT
-do-not-check-capabilities
flag
If set, classifier capabilities are not checked before classifier is built
(use with caution).
C
option
3
Number of sub-committees. (Default 3)
I
option
10
Number of iterations.
(default 10)
P
option
100
Percentage of weight mass to base training on.
(default 100, reduce to around 90 speed up)
Q
flag
Use resampling for boosting.
S
option
1
Random number seed.
(default 1)
W
baselearner
weka.classifiers.functions.MultilayerPerceptron
Full name of base classifier.
(default: weka.classifiers.trees.DecisionStump)
output-debug-info
flag
If set, classifier is run in debug mode and
may output additional info to the console
W
416
2
weka.MultilayerPerceptron
2
Weka_3.7.12-SNAPSHOT_10169
Weka implementation of MultilayerPerceptron
2014-08-18T16:50:53
English
Weka_3.7.12-SNAPSHOT
-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).
output-debug-info
flag
If set, classifier is run in debug mode and
may output additional info to the console
Verified_Learning_Curve,Verified_Supervised_Classification
Verified_Learning_Curve,Verified_Supervised_Classification
https://api.openml.org/data/download/54579/weka.classifiers.meta.MultiBoostAB7544332309784210095.class
class
78979b05808a5eec6b8776b175819763