252
2
weka.RotationForest_PrincipalComponents_ZeroR
1
Weka_3.7.10_8108
Juan J. Rodriguez, Ludmila I. Kuncheva, Carlos J. Alonso (2006). Rotation Forest: A new classifier ensemble method. IEEE Transactions on Pattern Analysis and Machine Intelligence. 28(10):1619-1630. URL http://doi.ieeecomputersociety.org/10.1109/TPAMI.2006.211.
2014-06-03T21:32:34
English
Weka_3.7.10
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
If set, classifier is run in debug mode and
may output additional info to the console
F
kernel
weka.filters.unsupervised.attribute.PrincipalComponents
Full class name of filter to use, followed
by filter options.
eg: "weka.filters.unsupervised.attribute.PrincipalComponents-R 1.0"
G
option
3
Minimum size of a group of attributes:
if numberOfGroups is true, the minimum number
of groups.
(default: 3)
H
option
3
Maximum size of a group of attributes:
if numberOfGroups is true, the maximum number
of groups.
(default: 3)
I
option
10
Number of iterations.
(default 10)
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
flag
Whether minGroup (-G) and maxGroup (-H) refer to
the number of groups or their size.
(default: false)
O
flag
Do not collapse tree.
P
option
50
Percentage of instances to be removed.
(default: 50)
Q
option
Seed for random data shuffling (default 1).
R
flag
Use reduced error pruning.
S
option
1
Random number seed.
(default 1)
U
flag
Use unpruned tree.
W
baselearner
weka.classifiers.rules.ZeroR
Full name of base classifier.
(default: weka.classifiers.trees.J48)
num-slots
option
1
Number of execution slots.
(default 1 - i.e. no parallelism)
W
56
1
weka.ZeroR
1
Weka_3.7.10_8034
Weka implementation of ZeroR
2014-04-04T14:38:33
English
Weka_3.7.10
D
flag
If set, classifier is run in debug mode and
may output additional info to the console
study_7
Verified_Learning_Curve,Verified_Supervised_Classification,Verified_Supervised_Data_Stream_Classification
F
244
2
weka.PrincipalComponents
1
Weka_3.7.10_8034
Weka implementation of PrincipalComponents
2014-06-03T21:18:32
English
Weka_3.7.10
A
option
5
Maximum number of attributes to include in
transformed attribute names.
(-1 = include all, default: 5)
C
flag
Center (rather than standardize) the
data and compute PCA using the covariance (rather
than the correlation) matrix.
M
option
-1
Maximum number of PC attributes to retain.
(-1 = include all, default: -1)
R
option
0.95
Retain enough PC attributes to account
for this proportion of variance in the original data.
(default: 0.95)
Verified_Supervised_Classification
https://api.openml.org/data/download/30703/weka.classifiers.meta.RotationForest2069562666615166061.class
class
c26fb92d6b30c61b4d3986535e42dd25