4295
1
weka.Bagging_MultilayerPerceptron
3
Weka_3.7.13_11465
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
2016-08-16T14:49:46
English
Weka_3.7.13
-do-not-check-capabilities
flag
If set, classifier capabilities are not checked before classifier is built
(use with caution).
-represent-copies-using-weights
flag
Represent copies of instances using weights rather than explicitly.
I
option
10
Number of iterations.
(default 10)
L
option
Maximum tree depth (default -1, no maximum)
M
option
Set minimum number of instances per leaf (default 2).
N
option
Number of folds for reduced error pruning (default 3).
O
flag
Calculate the out of bag error.
P
option
100
Size of each bag, as a percentage of the
training set size. (default 100)
R
flag
Spread initial count over all class values (i.e. don't use 1 per value)
S
option
1
Random number seed.
(default 1)
V
option
Set minimum numeric class variance proportion
of train variance for split (default 1e-3).
W
baselearner
weka.classifiers.functions.MultilayerPerceptron
Full name of base classifier.
(default: weka.classifiers.trees.REPTree)
num-decimal-places
option
The number of decimal places for the output of numbers in the model (default 2).
num-slots
option
1
Number of execution slots.
(default 1 - i.e. no parallelism)
(use 0 to auto-detect number of cores)
output-debug-info
flag
If set, classifier is run in debug mode and
may output additional info to the console
W
1820
767
weka.MultilayerPerceptron
4
Weka_3.7.13_10169
Weka implementation of MultilayerPerceptron
2015-11-25T19:00:43
English
Weka_3.7.13
-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).
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
study_15
study_20
study_34
study_73
Verified_Learning_Curve,Verified_Supervised_Classification
weka
weka_3.7.13
https://api.openml.org/data/download/1682546/weka.classifiers.functions.MultilayerPerceptron4217900601518466169.class
class
9f3d66acadd8b011519791d8c12b4f35
Verified_Learning_Curve,Verified_Supervised_Classification
weka
weka_3.7.13
https://api.openml.org/data/download/4538134/weka.classifiers.meta.Bagging7042671548180458317.class
class
656bf8da26e0af26022f2826e81a341f