/** * Sets the percentage of data to put in the training partition. Must be * greater than 0.0 and less than 1.0. * * @param trainingPercent The percentage of data to put in the training * partition. */ public void setTrainingPercent( final double trainingPercent) { RandomDataPartitioner.checkTrainingPercent(trainingPercent); this.trainingPercent = trainingPercent; }
/** * Randomly partitions the given data into a training and testing set. * * @param data The data to partition. * @return The data partitioned according to the training percentage. */ public PartitionedDataset<DataType> createPartition( final Collection<? extends DataType> data) { return RandomDataPartitioner.createPartition(data, this.getTrainingPercent(), this.getRandom()); }
/** * Creates a new instance of RandomDataPartitioner. * * @param trainingPercent The percentage of training data. * @param random The Random object to use. */ public RandomDataPartitioner( final double trainingPercent, final Random random) { super(random); this.setTrainingPercent(trainingPercent); }
/** * Randomly partitions the given data into a training and testing set. * * @param data The data to partition. * @return The data partitioned according to the training percentage. */ public PartitionedDataset<DataType> createPartition( final Collection<? extends DataType> data) { return RandomDataPartitioner.createPartition(data, this.getTrainingPercent(), this.getRandom()); }
/** * Creates a new instance of RandomDataPartitioner. * * @param trainingPercent The percentage of training data. * @param random The Random object to use. */ public RandomDataPartitioner( final double trainingPercent, final Random random) { super(random); this.setTrainingPercent(trainingPercent); }
/** * Sets the percentage of data to put in the training partition. Must be * greater than 0.0 and less than 1.0. * * @param trainingPercent The percentage of data to put in the training * partition. */ public void setTrainingPercent( final double trainingPercent) { RandomDataPartitioner.checkTrainingPercent(trainingPercent); this.trainingPercent = trainingPercent; }
/** * Randomly partitions the given data into a training and testing set. * * @param data The data to partition. * @return The data partitioned according to the training percentage. */ public PartitionedDataset<DataType> createPartition( final Collection<? extends DataType> data) { return RandomDataPartitioner.createPartition(data, this.getTrainingPercent(), this.getRandom()); }
/** * Creates a new instance of RandomDataPartitioner. * * @param trainingPercent The percentage of training data. * @param random The Random object to use. */ public RandomDataPartitioner( final double trainingPercent, final Random random) { super(random); this.setTrainingPercent(trainingPercent); }
/** * Sets the percentage of data to put in the training partition. Must be * greater than 0.0 and less than 1.0. * * @param trainingPercent The percentage of data to put in the training * partition. */ public void setTrainingPercent( final double trainingPercent) { RandomDataPartitioner.checkTrainingPercent(trainingPercent); this.trainingPercent = trainingPercent; }
/** * Creates a new instance of RandomDataPartitioner. */ public RandomDataPartitioner() { super(new Random()); this.setTrainingPercent(DEFAULT_TRAINING_PERCENT); }
RandomDataPartitioner.checkTrainingPercent(trainingPercent);
/** * Creates a new instance of RandomDataPartitioner. */ public RandomDataPartitioner() { super(new Random()); this.setTrainingPercent(DEFAULT_TRAINING_PERCENT); }
RandomDataPartitioner.checkTrainingPercent(trainingPercent);
/** * Creates a new instance of RandomDataPartitioner. */ public RandomDataPartitioner() { super(new Random()); this.setTrainingPercent(DEFAULT_TRAINING_PERCENT); }
RandomDataPartitioner.checkTrainingPercent(trainingPercent);