com.rapidminer.operator.learner.functions
Class LogisticRegressionOptimization
java.lang.Object
com.rapidminer.tools.math.optimization.ec.es.ESOptimization
com.rapidminer.operator.learner.functions.LogisticRegressionOptimization
- All Implemented Interfaces:
- Optimization
public class LogisticRegressionOptimization
- extends ESOptimization
Evolutionary Strategy approach for optimization of the logistic regression problem.
- Author:
- Ingo Mierswa, Tobias Malbrecht
Fields inherited from class com.rapidminer.tools.math.optimization.ec.es.ESOptimization |
BOLTZMANN_SELECTION, CUT_SELECTION, GAUSSIAN_MUTATION, INIT_TYPE_MAX, INIT_TYPE_MIN, INIT_TYPE_ONE, INIT_TYPE_RANDOM, INIT_TYPE_ZERO, MUTATION_TYPES, NO_MUTATION, NON_DOMINATED_SORTING_SELECTION, PARAMETER_CROSSOVER_PROB, PARAMETER_GENERATIONS_WITHOUT_IMPROVAL, PARAMETER_KEEP_BEST, PARAMETER_MAX_GENERATIONS, PARAMETER_MUTATION_TYPE, PARAMETER_POPULATION_SIZE, PARAMETER_SELECTION_TYPE, PARAMETER_SHOW_CONVERGENCE_PLOT, PARAMETER_SPECIFIY_POPULATION_SIZE, PARAMETER_TOURNAMENT_FRACTION, PARAMETER_USE_EARLY_STOPPING, POPULATION_INIT_TYPES, RANK_SELECTION, ROULETTE_WHEEL, SELECTION_TYPES, SPARSITY_MUTATION, STOCHASTIC_UNIVERSAL, SWITCHING_MUTATION, TOURNAMENT_SELECTION, UNIFORM_SELECTION |
Constructor Summary |
LogisticRegressionOptimization(ExampleSet exampleSet,
boolean addIntercept,
int initType,
int maxIterations,
int generationsWithoutImprovement,
int popSize,
int selectionType,
double tournamentFraction,
boolean keepBest,
int mutationType,
double crossoverProb,
boolean showConvergencePlot,
RandomGenerator random,
LoggingHandler logging)
Creates a new evolutionary optimization. |
Methods inherited from class com.rapidminer.tools.math.optimization.ec.es.ESOptimization |
evaluate, evaluate, evaluateAll, getBestFitnessEver, getBestFitnessInGeneration, getBestPerformanceEver, getBestValuesEver, getGeneration, getMax, getMin, getParameterTypes, getPopulation, getValueType, increaseCurrentEvaluationCounter, increaseTotalEvaluationCounter, optimize, setMax, setMin, setValueType |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
LogisticRegressionOptimization
public LogisticRegressionOptimization(ExampleSet exampleSet,
boolean addIntercept,
int initType,
int maxIterations,
int generationsWithoutImprovement,
int popSize,
int selectionType,
double tournamentFraction,
boolean keepBest,
int mutationType,
double crossoverProb,
boolean showConvergencePlot,
RandomGenerator random,
LoggingHandler logging)
- Creates a new evolutionary optimization.
evaluateIndividual
public PerformanceVector evaluateIndividual(Individual individual)
- Description copied from class:
ESOptimization
- Subclasses must implement this method to calculate the fitness of the
given individual. Please note that null might be returned for non-valid
individuals. The fitness will be maximized.
- Specified by:
evaluateIndividual
in class ESOptimization
train
public LogisticRegressionModel train()
throws OperatorException
- Throws:
OperatorException
nextIteration
public void nextIteration()
- Description copied from class:
ESOptimization
- This method is invoked after each evaluation. The default implementation
does nothing but subclasses might implement this method to support online
plotting or logging.
- Overrides:
nextIteration
in class ESOptimization
getPerformance
public PerformanceVector getPerformance()
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