com.bayesserver.inference

Interface Inference

All Known Implementing Classes:

LikelihoodSamplingInference, LoopyBeliefInference, RelevanceTreeInference, VariableEliminationInference

public interface Inference

The interface for a Bayesian network inference algorithm, which is used to perform queries such as calculating posterior probabilities and log-likelihood values for a case. For an example of a class that implements this interface see RelevanceTreeInference.

Method Summary

Modifier and Type	Method and Description
Evidence	getBaseEvidence() Optional evidence which can be used to calculate the lift of queries.
Evidence	getEvidence() Represents the evidence, or case data (e.g.
Network	getNetwork() The target Bayesian network.
QueryDistributionCollection	getQueryDistributions() Gets the collection of distributions to calculate.
QueryFunctionCollection	getQueryFunctions() Gets the collection of functions to evaluate, after QueryDistributions have been calculated.
void	query(QueryOptions queryOptions, QueryOutput queryOutput) Calculates a number of distributions, e.g.
void	setBaseEvidence(Evidence value) Optional evidence which can be used to calculate the lift of queries.
void	setEvidence(Evidence value) Represents the evidence, or case data (e.g.
void	setQueryDistributions(QueryDistributionCollection value) Sets the collection of distributions to calculate.
void	setQueryFunctions(QueryFunctionCollection value) Sets the collection of functions to evaluate, after QueryDistributions have been calculated.

Method Detail

getNetwork

Network getNetwork()

The target Bayesian network.

getEvidence

Evidence getEvidence()

Represents the evidence, or case data (e.g. row in a database) used in a query. The distributions are only recalculated by query(com.bayesserver.inference.QueryOptions, com.bayesserver.inference.QueryOutput), not each time evidence is changed.

For more information see Evidence.

setEvidence

void setEvidence(Evidence value)

Represents the evidence, or case data (e.g. row in a database) used in a query. The distributions are only recalculated by query(com.bayesserver.inference.QueryOptions, com.bayesserver.inference.QueryOutput), not each time evidence is changed.

For more information see Evidence.

getBaseEvidence

Evidence getBaseEvidence()

Optional evidence which can be used to calculate the lift of queries. Defaults to null. When QueryDistribution.getComparison() is true queries are adjusted based on marginals calculated with this evidence or no evidence if this value is null.

See Also:

QueryDistribution.getComparison()

setBaseEvidence

void setBaseEvidence(Evidence value)

Optional evidence which can be used to calculate the lift of queries. Defaults to null. When QueryDistribution.getComparison() is true queries are adjusted based on marginals calculated with this evidence or no evidence if this value is null.

See Also:

QueryDistribution.getComparison()

getQueryDistributions

QueryDistributionCollection getQueryDistributions()

Gets the collection of distributions to calculate. See QueryDistributionCollection. If required, a query distribution collection can be dynamically attached or detached. Also note that individual elements can be enabled or disabled on a per query basis.

setQueryDistributions

void setQueryDistributions(QueryDistributionCollection value)

Sets the collection of distributions to calculate. See QueryDistributionCollection. If required, a query distribution collection can be dynamically attached or detached. Also note that individual elements can be enabled or disabled on a per query basis.

getQueryFunctions

QueryFunctionCollection getQueryFunctions()

Gets the collection of functions to evaluate, after QueryDistributions have been calculated. If required, a query function collection can be dynamically attached or detached. Also note that individual elements can be enabled or disabled on a per query basis.

setQueryFunctions

void setQueryFunctions(QueryFunctionCollection value)

Sets the collection of functions to evaluate, after QueryDistributions have been calculated. If required, a query function collection can be dynamically attached or detached. Also note that individual elements can be enabled or disabled on a per query basis.

query

void query(QueryOptions queryOptions,
           QueryOutput queryOutput)
    throws InconsistentEvidenceException

Calculates a number of distributions, e.g. P(A) and P(B) given the evidence (case data, e.g. row in a database), and if requested the log-likelihood of the data. Each time this method is called the distributions have their values replaced, acting like buffers.

As well as requesting distributions of the form P(A), P(B) it is also possible to request distributions over a number of variables such as P(A,B).

If CLGaussian distributions are requested that include instantiated discrete variables, an algorithm may legitimately return mean and covariance values equal to NaN for entries corresponding to inconsistent discrete combinations. For example, if a CLGaussian is requested that includes a discrete variable 'Gender' with states 'Male' and 'Female' and evidence is set to 'Female' then any mean and covariance entries that correspond to 'Male' may be set to NaN. NaN values will always be accompanied by a corresponding zero value in the CLGaussian.getTable().

Parameters:

queryOptions - Options governing which calculations are performed and how.

queryOutput - Returns any information, in addition to the distributions, that is requested. For example the log-likelihood.

Throws:

InvalidNetworkException - Raised if the network is invalid.

InconsistentEvidenceException - Raised if inconsistent evidence is detected, or underflow/overflow occurs when calculating queries or the conflict measure. Note that log-likelihood calculations do not raise this exception, but instead report -Infinity or +Infinity.