Example usage for Java org.apache.mahout.classifier.sgd OnlineLogisticRegression fields, constructors, methods, implement or subclass
The text is from its open source code.
| int | stepOffset |
| OnlineLogisticRegression(int numCategories, int numFeatures, PriorFunction prior) | |
| OnlineLogisticRegression() |
| OnlineLogisticRegression | alpha(double alpha) Chainable configuration option. |
| Vector | classify(Vector instance) Returns n-1 probabilities, one for each category but the 0-th. |
| Vector | classifyFull(Vector r, Vector instance) Computes and returns a vector containing n scores, where n is numCategories() , given an input vector instance . |
| Vector | classifyFull(Vector instance) Computes and returns a vector containing n scores, where n is numCategories() , given an input vector instance . |
| double | classifyScalar(Vector instance) Returns a single scalar probability in the case where we have two categories. |
| void | close() |
| double | currentLearningRate() |
| OnlineLogisticRegression | decayExponent(double decayExponent) |
| Matrix | getBeta() |
| OnlineLogisticRegression | lambda(double lambda) |
| OnlineLogisticRegression | learningRate(double learningRate) Chainable configuration option. |
| double | logLikelihood(int actual, Vector data) Returns a measure of how good the classification for a particular example actually is. |
| int | numCategories() |
| int | numFeatures() |
| void | setBeta(int i, int j, double betaIJ) |
| void | train(int actual, Vector instance) |
| void | write(DataOutput out) |