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A
argMax(double[])
- Method in class ir.classifiers.
Classifier
Returns the array index with the maximum value
B
BayesResult
- class ir.classifiers.
BayesResult
.
An object to hold the result of training a NaiveBayes classifier.
BayesResult()
- Constructor for class ir.classifiers.
BayesResult
binExamples()
- Method in class ir.classifiers.
CVLearningCurve
Set the fold Bins from the total Examples -- this effectively stores the training-test split
C
calculatePriors(Vector)
- Method in class ir.classifiers.
NaiveBayes
Calculates the class priors
calculateProbs(Example)
- Method in class ir.classifiers.
NaiveBayes
Calculates the prob of the testExample being generated by each category
Categories
- Variable in class ir.classifiers.
NaiveBayes
Vector of categories (classes) in the data
category
- Variable in class ir.classifiers.
Example
Category index of the example
CLASSES
- Static variable in class ir.classifiers.
CVLearningCurve
Stores the possible class labels
classifier
- Variable in class ir.classifiers.
CVLearningCurve
The classifier for which K-fold CV learning curve has to be generated
Classifier
- class ir.classifiers.
Classifier
.
Abstract class specifying the functionality of a classifier.
Classifier()
- Constructor for class ir.classifiers.
Classifier
classPriors
- Variable in class ir.classifiers.
BayesResult
Stores the prior probabilities of each class
conditionalProbs(Vector)
- Method in class ir.classifiers.
NaiveBayes
Calculates the conditional probs of each feature in the different categories
CVLearningCurve
- class ir.classifiers.
CVLearningCurve
.
Gives learning curves with K-fold cross validation for a classifier.
D
debug
- Variable in class ir.classifiers.
NaiveBayes
Flag for debug prints
debug
- Variable in class ir.classifiers.
CVLearningCurve
Flag for debug display
debug
- Variable in class ir.classifiers.
KNN
displayProbs(double[], Hashtable)
- Method in class ir.classifiers.
NaiveBayes
Displays the probs for each feature in the different categories
document
- Variable in class ir.classifiers.
Example
fileDocument object for the example
E
EPSILON
- Variable in class ir.classifiers.
NaiveBayes
Small value to be used instead of 0 in probabilities, if Laplace smoothing is not used
Example
- class ir.classifiers.
Example
.
An object to hold training or test examples for categorization.
Example(HashMapVector, int, String, FileDocument)
- Constructor for class ir.classifiers.
Example
F
featureTable
- Variable in class ir.classifiers.
BayesResult
Stores the counts for each feature: an entry in the hashTable stores the array of class counts for a feature
findClassID(String)
- Static method in class ir.classifiers.
CVLearningCurve
Finds the class ID from the name of the document
foldBins
- Variable in class ir.classifiers.
CVLearningCurve
foldBins[i][j] stores the examples for class i in fold j.
G
getCategory()
- Method in class ir.classifiers.
Example
Returns the category of the example
getClassifier()
- Method in class ir.classifiers.
CVLearningCurve
Return classifier
getClassPriors()
- Method in class ir.classifiers.
BayesResult
Returns the class priors
getCVPredictions()
- Method in class ir.classifiers.
CVLearningCurve
Generate a vector of predictions ready for processing, by performing a cross-validation on the supplied dataset.
getDocument()
- Method in class ir.classifiers.
Example
Returns the document of the example
getEpsilon()
- Method in class ir.classifiers.
NaiveBayes
Returns value of EPSILON
getFeatureTable()
- Method in class ir.classifiers.
BayesResult
Returns the feature hash
getFoldBins()
- Method in class ir.classifiers.
CVLearningCurve
Return the fold Bins
getHashMapVector()
- Method in class ir.classifiers.
Example
Returns the hashVector of the example
getIsLaplace()
- Method in class ir.classifiers.
NaiveBayes
Returns value of isLaplace
getName()
- Method in class ir.classifiers.
Classifier
To be overloaded by the extending class
getName()
- Method in class ir.classifiers.
NaiveBayes
Returns the name
getName()
- Method in class ir.classifiers.
Rocchio
Returns the name
getName()
- Method in class ir.classifiers.
KNN
Returns the name
getName()
- Method in class ir.classifiers.
Example
Returns the name of the example
getTestCV(int)
- Method in class ir.classifiers.
CVLearningCurve
Creates the testing set for one fold of a cross-validation on the dataset.
getTestPrediction(Vector, Vector)
- Method in class ir.classifiers.
CVLearningCurve
Generate a prediction vector by performing an evaluation on the test set after training on the given training set.
getTotalExamples()
- Method in class ir.classifiers.
CVLearningCurve
Return all the examples
getTrainCV(int, double)
- Method in class ir.classifiers.
CVLearningCurve
Creates the training set for one fold of a cross-validation on the dataset.
getTrainResult()
- Method in class ir.classifiers.
NaiveBayes
Returns training result
H
hashVector
- Variable in class ir.classifiers.
Example
Representation of the example as a vector of (feature -> weight) mappings
I
ir.classifiers
- package ir.classifiers
isLaplace
- Variable in class ir.classifiers.
NaiveBayes
Flag to set Laplace smoothing when estimating probabilities
K
K
- Variable in class ir.classifiers.
Rocchio
K
- Variable in class ir.classifiers.
KNN
KNN
- class ir.classifiers.
KNN
.
M
main(String[])
- Static method in class ir.classifiers.
TestClassifier
N
NaiveBayes
- class ir.classifiers.
NaiveBayes
.
Implements the NaiveBayes Classifier with Laplace smoothing.
NaiveBayes(String[], boolean)
- Constructor for class ir.classifiers.
NaiveBayes
Create an naive bayes classifier with these attributes
name
- Static variable in class ir.classifiers.
NaiveBayes
Name of classifier
name
- Variable in class ir.classifiers.
Rocchio
name
- Variable in class ir.classifiers.
KNN
name
- Variable in class ir.classifiers.
Example
Name of the example
numCategories
- Variable in class ir.classifiers.
NaiveBayes
Number of categories
numClasses
- Variable in class ir.classifiers.
CVLearningCurve
Number of classes in the data
numExamples
- Variable in class ir.classifiers.
NaiveBayes
Number of training examples, set by train function
numFeatures
- Variable in class ir.classifiers.
NaiveBayes
Number of features
numFolds
- Variable in class ir.classifiers.
CVLearningCurve
Number of folds of cross validation to run
P
POINTS
- Static variable in class ir.classifiers.
CVLearningCurve
Points at which the learning curve is plotted
R
Rocchio
- class ir.classifiers.
Rocchio
.
rocchioMeanVectors
- Variable in class ir.classifiers.
Rocchio
S
setCategories(String[])
- Method in class ir.classifiers.
NaiveBayes
Set vector of categories (classes) in the data with the input string of categories
setCategory(int)
- Method in class ir.classifiers.
Example
Sets the category of the example
setClassifier(Classifier)
- Method in class ir.classifiers.
CVLearningCurve
Set the classifier
setClassPriors(double[])
- Method in class ir.classifiers.
BayesResult
Sets the class priors
setDebug(boolean)
- Method in class ir.classifiers.
NaiveBayes
Sets the debug flag
setDocument(FileDocument)
- Method in class ir.classifiers.
Example
Sets the document of the example
setEpsilon(double)
- Method in class ir.classifiers.
NaiveBayes
Sets the value of EPSILON (default 1e-6)
setFeatureTable(Hashtable)
- Method in class ir.classifiers.
BayesResult
Sets the feature hash
setFoldBins(Vector[][])
- Method in class ir.classifiers.
CVLearningCurve
Set the fold Bins
setHashMapVector(HashMapVector)
- Method in class ir.classifiers.
Example
Sets the hashVector of the example
setInvertedIndex(InvertedIndex)
- Method in class ir.classifiers.
Classifier
For classifiers that use invertedIndices, this function sets them -- needed for efficient memory management
setInvertedIndex(InvertedIndex)
- Method in class ir.classifiers.
NaiveBayes
Since NaiveBayes does not use an inverted Index, this function does nothing in the case of NaiveBayes
setInvertedIndex(InvertedIndex)
- Method in class ir.classifiers.
Rocchio
setInvertedIndex(InvertedIndex)
- Method in class ir.classifiers.
KNN
setLaplace(boolean)
- Method in class ir.classifiers.
NaiveBayes
Sets the Laplace smoothing flag
setName(String)
- Method in class ir.classifiers.
Example
Sets the name of the example
setTotalExamples(String)
- Method in class ir.classifiers.
CVLearningCurve
Sets the totalExamples by reading in file from directory dirName
setTotalExamples(Vector[])
- Method in class ir.classifiers.
CVLearningCurve
Set all the examples
T
test(Example)
- Method in class ir.classifiers.
Classifier
Returns true if the predicted category of the test example matches the correct category, false otherwise
test(Example)
- Method in class ir.classifiers.
NaiveBayes
Categorizes the test example using the trained Naive Bayes classifier, returning true if the predicted category is same as the actual category
test(Example)
- Method in class ir.classifiers.
Rocchio
test(Example)
- Method in class ir.classifiers.
KNN
TestClassifier
- class ir.classifiers.
TestClassifier
.
Wrapper class to test classifiers using k-fold CV.
TestClassifier()
- Constructor for class ir.classifiers.
TestClassifier
testTime
- Variable in class ir.classifiers.
CVLearningCurve
Total Testing time
toString()
- Method in class ir.classifiers.
Example
Returns the String representation of the example object
totalExamples
- Variable in class ir.classifiers.
CVLearningCurve
Stores all the examples for each class
train(Vector)
- Method in class ir.classifiers.
Classifier
Trains the classifier on the training examples
train(Vector)
- Method in class ir.classifiers.
NaiveBayes
Trains the Naive Bayes classifier - estimates the prior probs and calculates the counts for each feature in different categories
train(Vector)
- Method in class ir.classifiers.
Rocchio
train(Vector)
- Method in class ir.classifiers.
KNN
trainDocs
- Variable in class ir.classifiers.
Rocchio
trainDocs
- Variable in class ir.classifiers.
KNN
trainResult
- Variable in class ir.classifiers.
NaiveBayes
Stores the training result, set by the train function
trainTime
- Variable in class ir.classifiers.
CVLearningCurve
Total Training time
U
usesInvertedIndex()
- Method in class ir.classifiers.
Classifier
To indicated whether this classifier uses inverted index
usesInvertedIndex()
- Method in class ir.classifiers.
NaiveBayes
Function to indicate that this class does not use an inverted index
usesInvertedIndex()
- Method in class ir.classifiers.
Rocchio
Function to indicate that this class uses an inverted index
usesInvertedIndex()
- Method in class ir.classifiers.
KNN
Function to indicate that this class uses an inverted index
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