Package | Description |
---|---|
pl.poznan.put.cs.idss.jrs.apriori | |
pl.poznan.put.cs.idss.jrs.cbr.rules | |
pl.poznan.put.cs.idss.jrs.classifiers | |
pl.poznan.put.cs.idss.jrs.core.db |
This package provides classes that can be used to access the data in a database.
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pl.poznan.put.cs.idss.jrs.core.isf |
This package contains classes for dealing with ISF file format.
|
pl.poznan.put.cs.idss.jrs.core.mem |
Implements decision table stored in memory with random and serial access.
|
pl.poznan.put.cs.idss.jrs.dominance | |
pl.poznan.put.cs.idss.jrs.pct | |
pl.poznan.put.cs.idss.jrs.reducts | |
pl.poznan.put.cs.idss.jrs.rules | |
pl.poznan.put.cs.idss.jrs.types |
Provides classes for wrapping anything you can put into decision table.
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Modifier and Type | Method | Description |
---|---|---|
Attribute |
ElementaryCondition.getAttribute() |
Constructor | Description |
---|---|
ElementaryCondition(int attributePrefType,
int typeOfUnion,
int attributeNumber,
Field value,
Attribute attribute) |
Modifier and Type | Method | Description |
---|---|---|
static void |
CBRRulesAdjustment.adjustCBRRulesForClassification(RulesContainer rulesContainer,
PairSimilarity[] similarityFunctions,
Attribute[] testAttributes) |
Takes rules container with decision rules induced by means of DRSA-CBR approach
(with
SimilarityCondition conditions) and adjust these rules
so they can be used to classify new examples from test memory container with given attributes. |
Constructor | Description |
---|---|
AttributeInfoWithSimilarityFunction(int attributeNumber,
Attribute attribute) |
Constructor for
AttributeInfoWithSimilarityFunction class. |
AttributeInfoWithSimilarityFunction(int attributeNumber,
Attribute[] attributes) |
Constructor for
AttributeInfoWithSimilarityFunction class. |
AttributeInfoWithSimilarityFunction(int attributeNumber,
Attribute[] attributes,
int attributeMeaningDescription,
int quantityOfAddedMinimalValuesIfLorenz) |
Constructor for
AttributeInfoWithSimilarityFunction class. |
AttributeInfoWithSimilarityFunction(int attributeNumber,
Attribute attribute,
int attributeMeaningDescription,
int quantityOfAddedMinimalValuesIfLorenz) |
Constructor for
AttributeInfoWithSimilarityFunction class. |
Modifier and Type | Method | Description |
---|---|---|
void |
DRSAClassificationMethod.setDecisionAttributePreferenceType(Attribute decisionAttribute) |
Sets preference type (COST or GAIN) of the decision attribute.
|
void |
DRSAMethod.setDecisionAttributePreferenceType(Attribute decisionAttribute) |
Sets preference type (COST or GAIN) of the decision attribute.
|
void |
RulesDRSAClassificationMethod.setDecisionAttributePreferenceType(Attribute decisionAttribute) |
Sets preference type (COST or GAIN) of the decision attribute.
|
void |
RulesHybridClassificationMethod.setDecisionAttributePreferenceType(Attribute decisionAttribute) |
Constructor | Description |
---|---|
DRSAClassificationMethod(UnionContainer container,
double consistencyLevel,
Attribute decisionAttribute) |
|
DRSAClassificationMethod(UnionContainer container,
Attribute decisionAttribute) |
|
RulesDRSAClassificationMethod(RulesContainer rulesContainer,
Attribute decisionAttribute) |
Constructor setting rules container and decision attribute preference type
|
RulesDRSAClassificationMethod(RulesContainer rulesContainer,
Attribute decisionAttribute,
int classificationType) |
Constructor setting rules container, decision attribute preference type and classification type
|
RulesDRSAClassificationMethod(Attribute decisionAttribute) |
Constructor setting decision attribute preference type
|
WekaClassificationMethod(Attribute[] attributes) |
|
WekaClassificationMethod(Attribute[] attributes,
int decisionAttributeIndex) |
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WekaClassificationMethod(weka.classifiers.Classifier classifier,
Attribute[] attributes) |
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WekaClassificationMethod(weka.classifiers.Classifier classifier,
Attribute[] attributes,
int decsionAttributeIndex) |
|
WekaDistributionClassificationMethod(Attribute[] attributes) |
|
WekaDistributionClassificationMethod(Attribute[] attributes,
int decisionAttributeIndex) |
|
WekaDistributionClassificationMethod(weka.classifiers.Classifier classifier,
Attribute[] attributes) |
|
WekaDistributionClassificationMethod(weka.classifiers.Classifier classifier,
Attribute[] attributes,
int decsionAttributeIndex) |
Modifier and Type | Method | Description |
---|---|---|
Attribute[] |
HSQLInput.getAttributes() |
Gets attributes
|
Attribute[] |
MySQLInput.getAttributes() |
Gets attributes
|
Modifier and Type | Method | Description |
---|---|---|
void |
HSQLOutput.setAttributes(Attribute[] attributes) |
Sets attributes
|
void |
MySQLOutput.setAttributes(Attribute[] attributes) |
Sets attributes
|
Modifier and Type | Method | Description |
---|---|---|
Attribute[] |
AttributesBuilder.build() |
Modifier and Type | Method | Description |
---|---|---|
Attribute |
MemoryContainer.getAttribute(int index) |
Gives direct access to specified attribute.
|
Attribute[] |
MemoryContainer.getAttributes() |
Gives an access to attributes.
|
static Attribute[] |
MemoryContainerAttrManager.getAttributes(MemoryContainer memoryContainer) |
Gets attrbiutes from mememory container.
|
Modifier and Type | Method | Description |
---|---|---|
static boolean |
AttributesMeaningsDescriptions.descriptionValidForAttribute(int description,
Attribute attribute) |
Checks if given attribute's meaning description is valid for given attribute.
|
static int |
AttributesMeaningsDescriptions.getAttributeMeaningDescription(Attribute attribute,
int memoryContainerType,
int evaluationSpaceUsed) |
Gets description of the meaning of given attribute, for given type of memory container
(
MemoryContainerDescription.INFORMATION_TABLE , MemoryContainerDescription.PCT or MemoryContainerDescription.SIMILARITY_TABLE )
and for given evaluation space (MemoryContainerDescription.PARETO or MemoryContainerDescription.LORENZ ) |
static int |
AttributesMeaningsDescriptions.getAttributeMeaningDescription(Attribute attribute,
java.lang.String predicate) |
Gets meaning of given attribute, using given predicate (meaning in textual form).
|
static int[] |
MemoryContainerAttrManager.getNumbersOfActiveDecisionAttributes(Attribute[] attributes) |
Gets numbers of all active decision attributes present in given array of attributes
|
static int |
MemoryContainerAttrManager.getQuantityOfActiveConditionCardinalGainCriteria(Attribute[] attributes) |
Gets quantity of active, condition (
attributes[i].getKind() == Attribute.NONE ),
cardinal (of type IntegerField , CardinalField or FloatField ) and gain
criteria (i.e. attributes with gain preference type assigned) from given array of attributes.Main goal of this method is to get the number of criteria that may be transformed to Lorenz evaluation space. |
void |
MemoryContainer.setAttributes(Attribute[] attributes) |
Sets the first row of the table - attributes.
|
Modifier and Type | Method | Description |
---|---|---|
static boolean |
Dominance.dominates(Example y,
Example x,
Attribute[] attributes,
byte[] mask) |
Checks cumulative dominance.
|
static java.util.List<Example> |
Dominance.getPDominated(Example x,
MemoryContainer exampleSet,
Attribute[] attributes) |
|
static java.util.List<Example> |
Dominance.getPDominating(Example x,
MemoryContainer exampleSet,
Attribute[] attributes) |
Modifier and Type | Method | Description |
---|---|---|
void |
EvaluationDifference2PreferenceIntensityDegree.writeDiscretizations(java.lang.String fileName,
Attribute[] attributes) |
Writes discretizations stored in this class to file with given name (path)
|
Modifier and Type | Method | Description |
---|---|---|
Attribute |
PercentsOfAttributesInReducts.getAttribute(int index) |
Modifier and Type | Method | Description |
---|---|---|
java.util.ArrayList<java.util.ArrayList<Attribute>> |
ReductsGenerator.getReductsAsAttributes() |
Constructor | Description |
---|---|
PercentsOfAttributesInReducts(Attribute[] attributes,
float[] percents) |
Constructor
|
Modifier and Type | Method | Description |
---|---|---|
Attribute |
AttributeInfo.getAttribute() |
Gets reference to the attribute for which this information was created.
Because of efficiency, reference to the field of this class, not its copy, is returned. |
Attribute[] |
Rule.getLearningAttributes() |
Gets array with attributes from learning memory container for which this rule was generated (gives direct access)
|
Attribute[] |
RulesContainer.getLearningAttributes() |
Gets attributes from learning memory container for which rules present in this rules' container have been induced.
Because of efficiency field of this class is returned. |
Modifier and Type | Method | Description |
---|---|---|
void |
AttributesWriter.writeAttributes(Attribute[] attributes) |
Writes information about given attributes to text file for which given class has been created.
|
Constructor | Description |
---|---|
AttributeInfo(int attributeNumber,
Attribute attribute) |
Constructor for
AttributeInfo class used to store number of attribute and reference to the attribute,
without coping that attribute. |
AttributeInfo(int attributeNumber,
Attribute[] attributes) |
Constructor for
AttributeInfo class used to store number of attribute and reference to the attribute
with given number, without coping that attribute. |
AttributeInfo(int attributeNumber,
Attribute[] attributes,
int attributeMeaningDescription,
int quantityOfAddedMinimalValuesIfLorenz) |
Constructor for
AttributeInfo class used to store number of attribute, description of its meaning,
quantity of added minimal values (only if attribute is from Lorenz evaluation space) and reference
to the attribute with given number, without coping that attribute. |
AttributeInfo(int attributeNumber,
Attribute attribute,
int attributeMeaningDescription,
int quantityOfAddedMinimalValuesIfLorenz) |
Constructor for
AttributeInfo class used to store number of attribute, description of its meaning,
quantity of added minimal values (only if attribute is from Lorenz evaluation space) and reference
to the attribute without coping that attribute. |
OptRule(int type,
int characteristicDecisionClassUsageTip,
Field characteristicDecisionClass,
ConditionValidator conditionValidator,
java.util.HashSet<Condition> conditions,
java.util.HashSet<Condition> decisions,
Attribute[] learningAttributes) |
Extends
Rule(int, int, Field, ConditionValidator, HashSet, HashSet, Attribute[]) constructor. |
Rule(int type,
int characteristicDecisionClassUsageTip,
Field characteristicDecisionClass,
ConditionValidator conditionValidator,
java.util.HashSet<Condition> conditions,
java.util.HashSet<Condition> decisions,
Attribute[] learningAttributes) |
Constructs rule of given type, for given characteristic decision class
and tip for its usage, from given conditions and decisions and for given attributes from learning memory container.
Stores references to condition validator and learning attributes, without coping. |
RulesContainer(java.lang.String rulesFormat,
double consistencyLevel,
Field[] classes,
Attribute[] learningAttributes) |
Constructor for
RulesContainer class, creating rules' container for given rules' format,
array with all possible values of decision attribute (can be null if unknown, but cannot be empty),
level of consistency and array with attributes from learning memory container. |
Modifier and Type | Field | Description |
---|---|---|
Attribute[] |
Metadata.attributes |
Information describing the attributes of a decision table.
|
Modifier and Type | Method | Description |
---|---|---|
void |
Attribute.copy(Attribute attribute) |
Takes all values from another attribute.
|
static boolean |
Metadata.hasDiscretization(Attribute[] attributes) |
Checks if there is any discretization information within the given
attributes' array.
|
Constructor | Description |
---|---|
Example(Attribute[] attribs) |
Creates an example with initial values taken from attributes.
|
Example(Attribute[] attribs,
Field[] fields) |
Creates an example with given values (which must be suitable to the attributes).
|
Metadata(Attribute[] attributes,
FileInfo fileInfo) |
Constructs a metadata object and puts information within.
|