oracle.dmt.odm.settings.algorithm
Class NaiveBayesSettings

java.lang.Object
  |
  +--oracle.dmt.odm.MiningObject
        |
        +--oracle.dmt.odm.settings.algorithm.MiningAlgorithmSettings
              |
              +--oracle.dmt.odm.settings.algorithm.NaiveBayesSettings
All Implemented Interfaces:
java.io.Serializable

public class NaiveBayesSettings
extends MiningAlgorithmSettings

An instance of NaiveBayesSettings is used to specify settings for the Naive Bayes algorithm. Two settings are available: singleton threshold and pairwise threshold, as described below.

Since:
9.0.1
See Also:
Serialized Form

Constructor Summary
NaiveBayesSettings(float singletonThreshold, float pairwiseThreshold)
          Creates NaiveBayesSettings instance.
 
Method Summary
TypeMethod
 float getPairwiseThreshold()
          Returns the pairwise threshold, a threshold on the count of the frequent item pairs.
 float getSingletonThreshold()
          Returns the singleton threshold, a threshold on the count of the frequent items.
 void setPairwiseThreshold(float pairwiseThreshold)
          Sets the pairwise threshold.
 void setSingletonThreshold(float singletonThreshold)
          Sets the singleton threshold.
 void validate()
          Validates the thresholds of the NaiveBayesSettings.
 
Methods inherited from class oracle.dmt.odm.settings.algorithm.MiningAlgorithmSettings
getMiningAlgorithm, getMiningAlgorithmName
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

NaiveBayesSettings

public NaiveBayesSettings(float singletonThreshold,
                          float pairwiseThreshold)
                   throws InvalidArgumentException
Creates NaiveBayesSettings instance. Setting the thresholds closer to 0 may result in a more accurate model, but it will take longer to build. Setting the thresholds closer to 1 may produce models faster, but with less accuracy. A reasonable starting point is 0.5 for each threshold.
Parameters:
singletonThreshold - a threshold on the count of the frequent items
pairwiseThreshold - a threshold on the count of the frequent item pairs
Throws:
InvalidArgumentException
- singletonThreshold < 0 or singletonThreshold > 1
- pairwiseThreshold < 0 or pairwiseThreshold > 1
Method Detail

getSingletonThreshold

public float getSingletonThreshold()
Returns the singleton threshold, a threshold on the count of the frequent items. An item is a frequent item if it is included in a sufficiently large number of transactions. The singleton threshold is expressed as a percentage of the number of profiles. Suppose that the total number of transactions that an item appears is k and the total number of profiles is P, and t is the singleton threshold expressed as a percentage of P (0.01 indicates 1 percent of P). Then, the item is a frequent item if k >= t*P.
Returns:
the singleton threshold

getPairwiseThreshold

public float getPairwiseThreshold()
Returns the pairwise threshold, a threshold on the count of the frequent item pairs. An item pair is a frequent item pair if the items in the pair are frequent items that occur together in sufficiently large number of profiles. Suppose that two distinct items occur together in k profiles, the total number of profiles that include the frequent items is P, and t is the threshold expressed in percentage (0.01 indicates 1 percent of P). Then the pair is a frequent item pair if k >= t*P.
Returns:
the pairwise threshold

setPairwiseThreshold

public void setPairwiseThreshold(float pairwiseThreshold)
Sets the pairwise threshold.
Parameters:
pairwiseThreshold - the threshold on the count of the frequent item pairs

setSingletonThreshold

public void setSingletonThreshold(float singletonThreshold)
Sets the singleton threshold.
Parameters:
float - singletonThreshold a threshold on the count of the frequent items.

validate

public void validate()
              throws MiningObjectException
Validates the thresholds of the NaiveBayesSettings.
Throws:
MiningObjectException
- singletonThreshold < 0 or singletonThreshold > 1
- pairwiseThreshold < 0 or pairwiseThreshold > 1