IClassification (Java-Naive-Bayes-Classifier-JNBC 2.0.4 API)

All Known Subinterfaces:

IClassificationExplained

All Known Implementing Classes:

ClassificationExplainedImpl, ClassificationImpl
```
public interface IClassification
```
Classification output : class probabilities and (optionally) the features and counters for explanation / audit trail

Author:

elian

Method Summary

All Methods Instance Methods Abstract Methods
Modifier and Type	Method	Description
`IClassProbability[]`	`getClassProbabilities()`	The ordered classes and probabilities.
`Map<String,Long>`	`getExplanationData()`	All the data needed to explain the results.
`Map<String,String>`	`getFeatures()`	The input features
`double`	`getLaplaceSmoothingAlpha()`	The alpha value used for Laplace smoothing
`boolean`	`isLaplaceSmoothed()`	Is Laplace smoothed?
`boolean`	`isLaplaceSmoothedVariant()`	If Laplace Smoothed With variant, then: likelyhood[i] = 1d * ((categoryCount + alpha) / (globalCount + globalCountCategories * alpha)) * product; otherwise: likelyhood[i] = 1d * categoryCount / globalCount * product;

- Method Detail
  - getClassProbabilities
```
IClassProbability[] getClassProbabilities()
```
    The ordered classes and probabilities.
    
    Returns:
    
    the classProbabilities : class name and probability (possibly the last class is 'Other')
  - getExplanationData
```
Map<String,Long> getExplanationData()
```
    All the data needed to explain the results.
    
    Returns:
    
    the explanation : list of features and counts
  - isLaplaceSmoothed
```
boolean isLaplaceSmoothed()
```
    Is Laplace smoothed?
    
    Returns:
    
    True if Laplace smoothed
  - isLaplaceSmoothedVariant
```
boolean isLaplaceSmoothedVariant()
```
    If Laplace Smoothed With variant, then: likelyhood[i] = 1d * ((categoryCount + alpha) / (globalCount + globalCountCategories * alpha)) * product; otherwise: likelyhood[i] = 1d * categoryCount / globalCount * product;
    
    Returns:
    
    If Laplace smothing variant used
  - getFeatures
```
Map<String,String> getFeatures()
```
    The input features
    
    Returns:
    
    The input features
  - getLaplaceSmoothingAlpha
```
double getLaplaceSmoothingAlpha()
```
    The alpha value used for Laplace smoothing
    
    Returns:
    
    The alpha value, usually 1.0