3478
939
weka.AttributeSelectedClassifier_GainRatioAttributeEval_Ranker_MultilayerPerceptron
1
Weka_3.7.13_11461
Weka implementation of AttributeSelectedClassifier
2016-04-15T01:13:33
English
Weka_3.7.13
-do-not-check-capabilities
flag
If set, classifier capabilities are not checked before classifier is built
(use with caution).
-doNotMakeSplitPointActualValue
flag
Do not make split point actual value.
A
flag
Laplace smoothing for predicted probabilities.
B
flag
Use binary splits only.
C
option
Set confidence threshold for pruning.
(default 0.25)
D
flag
Output debugging info.
E
baselearner
weka.attributeSelection.GainRatioAttributeEval
Full class name of attribute evaluator, followed
by its options.
eg: "weka.attributeSelection.CfsSubsetEval -L"
(default weka.attributeSelection.CfsSubsetEval)
J
flag
Do not use MDL correction for info gain on numeric attributes.
L
flag
Do not clean up after the tree has been built.
M
option
Set minimum number of instances per leaf.
(default 2)
N
option
Set number of folds for reduced error
pruning. One fold is used as pruning set.
(default 3)
O
flag
Do not collapse tree.
P
option
The size of the thread pool, for example, the number of cores in the CPU. (default 1)
Q
option
Seed for random data shuffling (default 1).
R
flag
Use reduced error pruning.
S
kernel
weka.attributeSelection.Ranker
Full class name of search method, followed
by its options.
eg: "weka.attributeSelection.BestFirst -D 1"
(default weka.attributeSelection.BestFirst)
U
flag
Use unpruned tree.
W
baselearner
weka.classifiers.functions.MultilayerPerceptron
Full name of base classifier.
(default: weka.classifiers.trees.J48)
Z
flag
Precompute the full correlation matrix at the outset, rather than compute correlations lazily (as needed) during the search. Use this in conjuction with parallel processing in order to speed up a backward search.
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
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
S
2118
780
weka.Ranker
3
Weka_3.7.13_11213
Weka implementation of Ranker
2015-12-04T23:53:19
English
Weka_3.7.13
N
option
-1
Specify number of attributes to select
P
option
Specify a starting set of attributes.
Eg. 1,3,5-7.
Any starting attributes specified are
ignored during the ranking.
T
option
-1.7976931348623157E308
Specify a theshold by which attributes
may be discarded from the ranking.
weka
weka_3.7.13
E
2138
780
weka.GainRatioAttributeEval
1
Weka_3.7.13_11215
Weka implementation of GainRatioAttributeEval
2015-12-05T11:08:21
English
Weka_3.7.13
M
flag
treat missing values as a seperate value.
weka
weka_3.7.13
Verified_Supervised_Classification
weka
weka_3.7.13
https://api.openml.org/data/download/1912415/weka.classifiers.meta.AttributeSelectedClassifier1624337606020690104.class
class
e33297e05015e5c2e3533a8e686b98eb