三大計算機視覺和機器學習庫的演算法彙總
阿新 • • 發佈：2019-01-29
2、Weka
下載地址：http://www.cs.waikato.ac.nz/ml/weka/downloading.html
LibSVM下載地址：http://www.csie.ntu.edu.tw/~cjlin/libsvm/
程式設計環境：Eclipse
版本：3.6
教程：doc\index.html
機器學習：
1)weka.classifiers.bayes
AODE
AODEsr
BayesianLogisticRegression
BayesNet
ComplementNaiveBayes
DMNBtext
HNB
NaiveBayes
NaiveBayesMultinomial
NaiveBayesMultinomialUpd
NaiveBayesSimple
NaiveBayesUpdateable
WAODE
2)weka.classifiers.functions
GaussianProcesses
IsotonicRegression
LeastMedSq
LibLINEAR
LibSVM
LinearRegression
Logistic
MultilayerPerceptron
PaceRegression
PLSClassifier
RBFNetwork
SimpleLinearRegression
SimpleLogistic
SMO
SMOreg
SPegasos
VotedPerceptron
Winnow
3)weka.classifiers.lazy
IB1
IBk
KStar
LBR
LWL
4)weka.classifiers.meta
AdaBoostM1
AdditiveRegression
AttributeSelectedClassifier
Bagging
ClassificationViaClustering
ClassificationViaRegression
CostSensitiveClassifier
CVParameterSelection
Dagging
Decorate
END
FilteredClassifier
Grading
GridSearch
LogitBoost
MetaCost
MultiBoostAB
MultiClassClassifier
MultiScheme
OrdinalClassClassifier
RacedIncrementalLogitBoost
RandomCommittee
RandomSubSpace
RegressionByDiscretization
RotationForest
Stacking
StackingC
ThresholdSelector
Vote
5)weka.classifiers.mi
CitationKNN
MDD
MIBoost
MIDD
MIEMDD
MILR
MINND
MIOptimalBall
MISMO
MISVM
MIWrapper
SimpleMI
6)weka.classifiers.rules
ConjunctiveRule
DecisionTable
DecisionTableHashKey
DTNB
JRip
M5Rules
NNge
OneR
PART
Prism
Ridor
Rule
RuleStats
ZeroR
7)weka.classifiers.trees
ADTree
BFTree
DecisionStump
FT
Id3
J48
J48graft
LADTree
LMT
M5P
NBTree
RandomForest
RandomTree
REPTree
SimpleCart
UserClassifier
8)weka.clusterers
AbstractClusterer
AbstractDensityBasedClusterer
CheckClusterer
CLOPE
ClusterEvaluation
Cobweb
DBSCAN
EM
FarthestFirst
FilteredClusterer
HierarchicalClusterer
MakeDensityBasedClusterer
OPTICS
RandomizableClusterer
RandomizableDensityBasedClusterer
RandomizableSingleClustererEnhancer
sIB
SimpleKMeans
SingleClustererEnhancer
XMeans
下載地址：http://www.cs.waikato.ac.nz/ml/weka/downloading.html
LibSVM下載地址：http://www.csie.ntu.edu.tw/~cjlin/libsvm/
程式設計環境：Eclipse
版本：3.6
教程：doc\index.html
機器學習：
1)weka.classifiers.bayes
AODE
AODEsr
BayesianLogisticRegression
BayesNet
ComplementNaiveBayes
DMNBtext
HNB
NaiveBayes
NaiveBayesMultinomial
NaiveBayesMultinomialUpd
NaiveBayesSimple
NaiveBayesUpdateable
WAODE
2)weka.classifiers.functions
GaussianProcesses
IsotonicRegression
LeastMedSq
LibLINEAR
LibSVM
LinearRegression
Logistic
MultilayerPerceptron
PaceRegression
PLSClassifier
RBFNetwork
SimpleLinearRegression
SimpleLogistic
SMO
SMOreg
SPegasos
VotedPerceptron
Winnow
3)weka.classifiers.lazy
IB1
IBk
KStar
LBR
LWL
4)weka.classifiers.meta
AdaBoostM1
AdditiveRegression
AttributeSelectedClassifier
Bagging
ClassificationViaClustering
ClassificationViaRegression
CostSensitiveClassifier
CVParameterSelection
Dagging
Decorate
END
FilteredClassifier
Grading
GridSearch
LogitBoost
MetaCost
MultiBoostAB
MultiClassClassifier
MultiScheme
OrdinalClassClassifier
RacedIncrementalLogitBoost
RandomCommittee
RandomSubSpace
RegressionByDiscretization
RotationForest
Stacking
StackingC
ThresholdSelector
Vote
5)weka.classifiers.mi
CitationKNN
MDD
MIBoost
MIDD
MIEMDD
MILR
MINND
MIOptimalBall
MISMO
MISVM
MIWrapper
SimpleMI
6)weka.classifiers.rules
ConjunctiveRule
DecisionTable
DecisionTableHashKey
DTNB
JRip
M5Rules
NNge
OneR
PART
Prism
Ridor
Rule
RuleStats
ZeroR
7)weka.classifiers.trees
ADTree
BFTree
DecisionStump
FT
Id3
J48
J48graft
LADTree
LMT
M5P
NBTree
RandomForest
RandomTree
REPTree
SimpleCart
UserClassifier
8)weka.clusterers
AbstractClusterer
AbstractDensityBasedClusterer
CheckClusterer
CLOPE
ClusterEvaluation
Cobweb
DBSCAN
EM
FarthestFirst
FilteredClusterer
HierarchicalClusterer
MakeDensityBasedClusterer
OPTICS
RandomizableClusterer
RandomizableDensityBasedClusterer
RandomizableSingleClustererEnhancer
sIB
SimpleKMeans
SingleClustererEnhancer
XMeans