Class GISModel

A maximum entropy model which has been trained using the Generalized Iterative Scaling procedure (implemented in GIS.java).

public sealed class GISModel : AbstractModel, IMaxentModel

Inherited Members: AbstractModel.GetBestOutcome(double[])

AbstractModel.GetModelType()

AbstractModel.GetAllOutcomes(double[])

AbstractModel.GetOutcome(int)

AbstractModel.GetIndex(string)

AbstractModel.NumOutcomes

AbstractModel.GetDataStructures()

AbstractModel.GetHashCode()

AbstractModel.Equals(object)

object.Equals(object, object)

object.GetType()

object.ReferenceEquals(object, object)

object.ToString()

Constructors

Creates a new model with the specified parameters, outcome names, and predicate/feature labels.

public GISModel(Context[] @params, string[] predLabels, string[] outcomeNames)

Creates a new model with the specified parameters, outcome names, and predicate/feature labels.

public GISModel(Context[] @params, string[] predLabels, string[] outcomeNames, IPrior prior)

Use this model to evaluate a context and return an array of the likelihood of each outcome given the specified context and the specified parameters.

public static double[] Eval(int[] context, double[] prior, EvalParameters model)

context int[]: The integer values of the predicates which have been observed at the present decision point.
prior double[]: The prior distribution for the specified context.
model EvalParameters: The set of parametes used in this computation.

double[]: The normalized probabilities for the outcomes given the context. The indexes of the double[] are the outcome ids, and the actual string representation of the outcomes can be obtained from the method getOutcome(int i).

Use this model to evaluate a context and return an array of the likelihood of each outcome given that context.

public override double[] Eval(string[] context)

context string[]: The names of the predicates which have been observed at the present decision point.

double[]: The normalized probabilities for the outcomes given the context. The indexes of the double[] are the outcome ids, and the actual string representation of the outcomes can be obtained from the method getOutcome(int i).

Evaluates a context.

public override double[] Eval(string[] context, double[] outsums)

context string[]: A list of String names of the contextual predicates which are to be evaluated together.
outsums double[]

double[]: an array of the probabilities for each of the different outcomes, all of which sum to 1.

Evaluates a contexts with the specified context values.

public override double[] Eval(string[] context, float[] values)

context string[]: A list of String names of the contextual predicates which are to be evaluated together.
values float[]: The values associated with each context.

double[]: an array of the probabilities for each of the different outcomes, all of which sum to 1.

Use this model to evaluate a context and return an array of the likelihood of each outcome given that context.

public double[] Eval(string[] context, float[]? values, double[] outsums)

context string[]: The names of the predicates which have been observed at the present decision point.
values float[]
outsums double[]: This is where the distribution is stored.

double[]: The normalized probabilities for the outcomes given the context. The indexes of the double[] are the outcome ids, and the actual string representation of the outcomes can be obtained from the method getOutcome(int i).