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public interface Algorithm
The algorithm interface for implementing variations of bayes Algorithm
Method Summary | |
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ClassifierResult |
classifyDocument(java.lang.String[] document,
Datastore datastore,
java.lang.String defaultCategory)
Classify the document and return the Result |
ClassifierResult[] |
classifyDocument(java.lang.String[] document,
Datastore datastore,
java.lang.String defaultCategory,
int numResults)
Classify the document and return the top numResults |
double |
documentWeight(Datastore datastore,
java.lang.String label,
java.lang.String[] document)
Calculate the document weight as the dot product of document vector and the corresponding weight vector of a particular class |
double |
featureWeight(Datastore datastore,
java.lang.String label,
java.lang.String feature)
Get the weighted probability of the feature. |
java.util.Collection<java.lang.String> |
getLabels(Datastore datastore)
Returns the labels in the given Model |
void |
initialize(Datastore datastore)
Initialize the data store and verifies the data in it. |
Method Detail |
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void initialize(Datastore datastore) throws InvalidDatastoreException
datastore
-
InvalidDatastoreException
ClassifierResult classifyDocument(java.lang.String[] document, Datastore datastore, java.lang.String defaultCategory) throws InvalidDatastoreException
document
- The document to classifydatastore
- The data store(InMemory, HBase)defaultCategory
- The default category to assign Ties are broken by comparing the category
ClassifierResult
s.
InvalidDatastoreException
ClassifierResult[] classifyDocument(java.lang.String[] document, Datastore datastore, java.lang.String defaultCategory, int numResults) throws InvalidDatastoreException
numResults
document
- The document to classifydatastore
- The Datastore
(InMemory, HBase)defaultCategory
- The default category to assignnumResults
- The maximum number of results to return, ranked by score. Ties are broken by comparing the
category
ClassifierResult
s.
InvalidDatastoreException
double featureWeight(Datastore datastore, java.lang.String label, java.lang.String feature) throws InvalidDatastoreException
datastore
- The Datastore
(InMemory, HBase)label
- The label of the featurefeature
- The feature to calc. the prob. for
InvalidDatastoreException
double documentWeight(Datastore datastore, java.lang.String label, java.lang.String[] document) throws InvalidDatastoreException
datastore
- The Datastore
(InMemory, HBase)label
- The label to calculate the probability ofdocument
- The document
InvalidDatastoreException
featureWeight(Datastore, String, String)
java.util.Collection<java.lang.String> getLabels(Datastore datastore) throws InvalidDatastoreException
datastore
- The Datastore
(InMemory, HBase)
Collection
of labels
InvalidDatastoreException
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