import com.rapidminer.operator.learner.igss.utility.Utility; //导入依赖的package包/类

@Override

public List getParameterTypes() {

List types = super.getParameterTypes();

ParameterType type = new ParameterTypeInt(PARAMETER_ITERATIONS, "the number of iterations", 1, 50, 10);

type.setExpert(false);

types.add(type);

type = new ParameterTypeBoolean(PARAMETER_FORCE_ITERATIONS,

"make all iterations even if termination criterion is met", false);

type.setExpert(false);

types.add(type);

types.add(new ParameterTypeDouble(PARAMETER_EPSILON, "approximation parameter", 0.01, 1.0, 0.04));

types.add(new ParameterTypeDouble(PARAMETER_DELTA, "desired confidence", 0.01, 1.0, 0.1));

types.add(new ParameterTypeDouble(PARAMETER_MIN_UTILITY_PRUNING, "minimum utility used for pruning", -1.0d, 1.0d,

0.0d));

types.add(new ParameterTypeDouble(PARAMETER_MIN_UTILITY_USEFUL, "minimum utility for the usefulness of a rule",

-1.0, 1.0, 0.0d));

types.add(new ParameterTypeInt(PARAMETER_STEPSIZE, "the number of examples drawn before the next hypothesis update",

1, 10000, 100));

types.add(new ParameterTypeInt(PARAMETER_LARGE,

"the number of examples a hypothesis must cover before normal approximation is used", 1, 10000, 100));

types.add(new ParameterTypeInt(PARAMETER_MAX_COMPLEXITY, "the maximum complexity of hypothesis", 1, 10, 1));

types.add(new ParameterTypeInt(PARAMETER_MIN_COMPLEXITY, "the minimum complexity of hypothesis", 1, 10, 1));

types.add(new ParameterTypeBoolean(PARAMETER_USE_BINOMIAL,

"Switch to binomial utility funtion before increasing complexity", false));

types.add(new ParameterTypeCategory(PARAMETER_UTILITY_FUNCTION, "the utility function to be used",

Utility.UTILITY_TYPES, 4));

types.add(new ParameterTypeBoolean(PARAMETER_USE_KBS, "use kbs to reweight examples after each iteration", true));

types.add(new ParameterTypeBoolean(PARAMETER_REJECTION_SAMPLING,

"use rejection sampling instead of weighted examples", true));

types.add(new ParameterTypeCategory(PARAMETER_USEFUL_CRITERION,

"criterion to decide if the complexity is increased ", IteratingGSS.CRITERION_TYPES, 1));

types.add(new ParameterTypeDouble(PARAMETER_EXAMPLE_FACTOR,

"used by example criterion to determine usefulness of a hypothesis", 1.0, 5.0, 1.5));

types.add(new ParameterTypeBoolean(PARAMETER_GENERATE_ALL_HYPOTHESIS, "generate h->Y+/Y- or h->Y+ only.", false));

types.add(new ParameterTypeBoolean(PARAMETER_RESET_WEIGHTS, "Set weights back to 1 when complexity is increased.",

false));

return types;

}