4016
1
weka.FilteredClassifier_MultiSearch_SMO_RBFKernel
1
Weka_3.7.13_11958
Weka implementation of FilteredClassifier
2016-06-13T14:36:53
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 binary attributes for discretized attributes.
E
flag
Use better encoding of split point for MDL.
F
option
weka.filters.supervised.attribute.Discretize -R first-last -precision 6
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.meta.MultiSearch
Full name of base classifier.
(default: weka.classifiers.trees.J48)
Y
flag
Use bin numbers rather than ranges for discretized attributes.
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
precision
option
Precision for bin boundary labels.
(default = 6 decimal places).
W
4017
1
weka.MultiSearch_SMO_RBFKernel
2
Weka_3.7.13_4521
Weka implementation of MultiSearch
2016-06-13T14:36:53
English
Weka_3.7.13
-do-not-check-capabilities
flag
If set, classifier capabilities are not checked before classifier is built
(use with caution).
C
flag
Do not try to eliminate colinear attributes.
E
option
CC
Determines the parameter used for evaluation:
CC = Correlation coefficient
MCC = Matthews correlation coefficient
RMSE = Root mean squared error
RRSE = Root relative squared error
MAE = Mean absolute error
RAE = Root absolute error
COMB = Combined = (1-abs(CC)) + RRSE + RAE
ACC = Accuracy
KAP = Kappa
PREC = Precision (per class)
WPREC = Weighted precision
REC = Recall (per class)
WREC = Weighted recall
AUC = Area under ROC (per class)
WAUC = Weighted area under ROC
PRC = Area under PRC (per class)
WPRC = Weighted area under PRC
FM = F-Measure (per class)
WFM = Weighted F-Measure
TPR = True positive rate (per class)
TNR = True negative rate (per class)
FPR = False positive rate (per class)
FNR = False negative rate (per class)
(default: CC)
R
option
Set ridge parameter (default 1.0e-8).
S
option
1
Random number seed.
(default 1)
W
baselearner
weka.classifiers.functions.SMO
Full name of base classifier.
(default: weka.classifiers.functions.LinearRegression)
additional-stats
flag
Output additional statistics.
algorithm
option
weka.classifiers.meta.multisearch.DefaultSearch -sample-size 100.0 -initial-folds 2 -subsequent-folds 10 -initial-test-set . -subsequent-test-set . -num-slots 1 -num-slots 1
A search algorithm.
class-label
option
1
The class label index to retrieve the metric for (if applicable).
log-file
option
/home/rijnjnvan/apps/weka-3-7-13
The log file to log the messages to.
(default: none)
minimal
flag
Conserve memory, don't keep dataset header and means/stdevs.
Model cannot be printed out if this option is enabled. (default: keep data)
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
search
array
A property search setup.
W
4018
1
weka.SMO_RBFKernel
7
Weka_3.7.13_10141
J. Platt: Fast Training of Support Vector Machines using Sequential Minimal Optimization. In B. Schoelkopf and C. Burges and A. Smola, editors, Advances in Kernel Methods - Support Vector Learning, 1998.
S.S. Keerthi, S.K. Shevade, C. Bhattacharyya, K.R.K. Murthy (2001). Improvements to Platt's SMO Algorithm for SVM Classifier Design. Neural Computation. 13(3):637-649.
Trevor Hastie, Robert Tibshirani: Classification by Pairwise Coupling. In: Advances in Neural Information Processing Systems, 1998.
2016-06-13T14:36:53
English
Weka_3.7.13
-do-not-check-capabilities
flag
If set, classifier capabilities are not checked before classifier is built
(use with caution).
C
option
1.0
The complexity constant C. (default 1)
E
option
The Exponent to use.
(default: 1.0)
K
kernel
weka.classifiers.functions.supportVector.RBFKernel
The Kernel to use.
(default: weka.classifiers.functions.supportVector.PolyKernel)
L
option
0.001
The tolerance parameter. (default 1.0e-3)
M
flag
Fit logistic models to SVM outputs.
N
option
0
Whether to 0=normalize/1=standardize/2=neither. (default 0=normalize)
P
option
1.0E-12
The epsilon for round-off error. (default 1.0e-12)
V
option
-1
The number of folds for the internal
cross-validation. (default -1, use training data)
W
option
1
The random number seed. (default 1)
no-checks
flag
Turns off all checks - use with caution!
Turning them off assumes that data is purely numeric, doesn't
contain any missing values, and has a nominal class. Turning them
off also means that no header information will be stored if the
machine is linear. Finally, it also assumes that no instance has
a weight equal to 0.
(default: checks on)
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
K
2231
2
weka.RBFKernel
4
Weka_3.7.13_11896
Weka implementation of RBFKernel
2015-12-22T15:22:05
English
Weka_3.7.13
C
option
250007
The size of the cache (a prime number), 0 for full cache and
-1 to turn it off.
(default: 250007)
G
option
0.01
The Gamma parameter.
(default: 0.01)
no-checks
flag
Turns off all checks - use with caution!
(default: checks on)
output-debug-info
flag
Enables debugging output (if available) to be printed.
(default: off)
weka
weka_3.7.13
weka
weka_3.7.13
weka
weka_3.7.13
study_14
Verified_Supervised_Classification
weka
weka_3.7.13
https://api.openml.org/data/download/2035719/weka.classifiers.meta.FilteredClassifier3824247799390133201.class
class
af48820ceb4953af57f4a2cbbbc4d9be