AutoFloatDataSet
org.encog.ml.data.auto

Class AutoFloatDataSet

    • Constructor Detail

      • AutoFloatDataSet

        public AutoFloatDataSet(int theInputCount,                int theIdealCount,                int theInputWindowSize,                int theOutputWindowSize)
    • Method Detail

      • getIdealSize

        public int getIdealSize()
        Specified by:
        getIdealSize in interface MLDataSet
        Returns:
        The size of the input data.
      • getInputSize

        public int getInputSize()
        Specified by:
        getInputSize in interface MLDataSet
        Returns:
        The size of the input data.
      • isSupervised

        public boolean isSupervised()
        Specified by:
        isSupervised in interface MLDataSet
        Returns:
        True if this is a supervised training set.
      • getRecordCount

        public long getRecordCount()
        Description copied from interface: MLDataSet
        Determine the total number of records in the set.
        Specified by:
        getRecordCount in interface MLDataSet
        Returns:
        The total number of records in the set.
      • getRecord

        public void getRecord(long index,             MLDataPair pair)
        Description copied from interface: MLDataSet
        Read an individual record, specified by index, in random order.
        Specified by:
        getRecord in interface MLDataSet
        Parameters:
        index - The index to read.
        pair - The pair that the record will be copied into.
      • openAdditional

        public MLDataSet openAdditional()
        Description copied from interface: MLDataSet
        Opens an additional instance of this dataset.
        Specified by:
        openAdditional in interface MLDataSet
        Returns:
        The new instance.
      • add

        public void add(MLData data1)
        Description copied from interface: MLDataSet
        Add a object to the dataset. This is used with unsupervised training, as no ideal output is provided. Note: not all implemenations support the add methods.
        Specified by:
        add in interface MLDataSet
        Parameters:
        data1 - The data item to be added.
      • add

        public void add(MLData inputData,       MLData idealData)
        Description copied from interface: MLDataSet
        Add a set of input and ideal data to the dataset. This is used with supervised training, as ideal output is provided. Note: not all implementations support the add methods.
        Specified by:
        add in interface MLDataSet
        Parameters:
        inputData - Input data.
        idealData - Ideal data.
      • add

        public void add(MLDataPair inputData)
        Description copied from interface: MLDataSet
        Add a an object to the dataset. This is used with unsupervised training, as no ideal output is provided. Note: not all implementations support the add methods.
        Specified by:
        add in interface MLDataSet
        Parameters:
        inputData - A MLDataPair object that contains both input and ideal data.
      • close

        public void close()
        Description copied from interface: MLDataSet
        Close this datasource and release any resources obtained by it, including any iterators created.
        Specified by:
        close in interface MLDataSet
      • size

        public int size()
        Specified by:
        size in interface MLDataSet
      • addColumn

        public void addColumn(float[] data)
      • loadCSV

        public void loadCSV(String filename,           boolean headers,           CSVFormat format,           int[] input,           int[] ideal)
      • getNormalizedMax

        public float getNormalizedMax()
        Returns:
        the normalizedMax
      • setNormalizedMax

        public void setNormalizedMax(float normalizedMax)
        Parameters:
        normalizedMax - the normalizedMax to set
      • getNormalizedMin

        public float getNormalizedMin()
        Returns:
        the normalizedMin
      • setNormalizedMin

        public void setNormalizedMin(float normalizedMin)
        Parameters:
        normalizedMin - the normalizedMin to set
      • isNormalizationEnabled

        public boolean isNormalizationEnabled()
        Returns:
        the normalizationEnabled
      • setNormalizationEnabled

        public void setNormalizationEnabled(boolean normalizationEnabled)
        Parameters:
        normalizationEnabled - the normalizationEnabled to set

SCaVis 1.8 © jWork.org