711
1
weka.FilteredClassifier_Discretize_J48
3
Weka_3.7.12-SNAPSHOT_11142
Weka implementation of FilteredClassifier
2014-11-15T12:57:53
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).
-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 binary attributes for discretized attributes.
E
flag
Use better encoding of split point for MDL.
F
kernel
weka.filters.supervised.attribute.Discretize
Full class name of filter to use, followed
by filter options.
eg: "weka.filters.unsupervised.attribute.Remove -V -R 1,2"
J
flag
Do not use MDL correction for info gain on numeric attributes.
K
flag
Use Kononenko's MDL criterion.
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.
Q
option
Seed for random data shuffling (default 1).
R
flag
Use reduced error pruning.
S
flag
Do not perform subtree raising.
U
flag
Use unpruned tree.
V
flag
Invert matching sense of column indexes.
W
baselearner
weka.classifiers.trees.J48
Full name of base classifier.
(default: weka.classifiers.trees.J48)
Y
flag
Use bin numbers rather than ranges for discretized attributes.
output-debug-info
flag
If set, classifier is run in debug mode and
may output additional info to the console
precision
option
Precision for bin boundary labels.
(default = 6 decimal places).
F
588
2
weka.Discretize
2
Weka_3.7.12-SNAPSHOT_10231
Usama M. Fayyad, Keki B. Irani: Multi-interval discretization of continuousvalued attributes for classification learning. In: Thirteenth International Joint Conference on Articial Intelligence, 1022-1027, 1993.
Igor Kononenko: On Biases in Estimating Multi-Valued Attributes. In: 14th International Joint Conference on Articial Intelligence, 1034-1040, 1995.
2014-10-07T15:41:16
English
Weka_3.7.12-SNAPSHOT
D
flag
Output binary attributes for discretized attributes.
E
flag
Use better encoding of split point for MDL.
K
flag
Use Kononenko's MDL criterion.
R
option
first-last
Specifies list of columns to Discretize. First and last are valid indexes.
(default none)
V
flag
Invert matching sense of column indexes.
Y
flag
Use bin numbers rather than ranges for discretized attributes.
precision
option
6
Precision for bin boundary labels.
(default = 6 decimal places).
W
675
2
weka.J48
13
Weka_3.7.12-SNAPSHOT_11194
Ross Quinlan (1993). C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA.
2014-10-30T11:53:26
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).
-doNotMakeSplitPointActualValue
flag
Do not make split point actual value.
A
flag
Laplace smoothing for predicted probabilities.
B
flag
Use binary splits only.
C
option
0.25
Set confidence threshold for pruning.
(default 0.25)
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
2
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.
Q
option
Seed for random data shuffling (default 1).
R
flag
Use reduced error pruning.
S
flag
Do not perform subtree raising.
U
flag
Use unpruned tree.
output-debug-info
flag
If set, classifier is run in debug mode and
may output additional info to the console
study_2
study_37
study_73
Verified_Learning_Curve,Verified_Supervised_Classification
https://api.openml.org/data/download/116690/weka.classifiers.trees.J483562716070411093887.class
class
6d8bbe1e017bcbd4d08fc5789ea9385e
curves
Verified_Learning_Curve
weka
weka_3.7.12-SNAPSHOT
https://api.openml.org/data/download/158699/weka.classifiers.meta.FilteredClassifier8235740895629556169.class
class
ee67ef8dace0cae2835a61defe36d1aa