Example usage for weka.core NoSupportForMissingValuesException NoSupportForMissingValuesException

Introduction

In this page you can find the example usage for weka.core NoSupportForMissingValuesException NoSupportForMissingValuesException.

Prototype

public NoSupportForMissingValuesException(String message) 

Source Link

Document

Creates a new NoSupportForMissingValuesException.

Usage

From source file:cerebro.Id3.java

License:Open Source License

/**
 * Classifies a given test instance using the decision tree.
 *
 * @param instance the instance to be classified
 * @return the classification/*  w  ww .  j av  a  2  s  .c o  m*/
 * @throws NoSupportForMissingValuesException if instance has missing values
 */
public double classifyInstance(Instance instance) throws NoSupportForMissingValuesException {

    if (instance.hasMissingValue()) {
        throw new NoSupportForMissingValuesException("Id3: no missing values, " + "please.");
    }
    if (m_Attribute == null) {
        return m_ClassValue;
    } else {
        return m_Successors[(int) instance.value(m_Attribute)].classifyInstance(instance);
    }
}

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From source file:cerebro.Id3.java

License:Open Source License

/**
 * Computes class distribution for instance using decision tree.
 *
 * @param instance the instance for which distribution is to be computed
 * @return the class distribution for the given instance
 * @throws NoSupportForMissingValuesException if instance has missing values
 *//*w  ww. j a  v  a 2  s. co  m*/
public double[] distributionForInstance(Instance instance) throws NoSupportForMissingValuesException {

    if (instance.hasMissingValue()) {
        throw new NoSupportForMissingValuesException("Id3: no missing values, " + "please.");
    }
    if (m_Attribute == null) {
        return m_Distribution;
    } else {
        return m_Successors[(int) instance.value(m_Attribute)].distributionForInstance(instance);
    }
}

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From source file:id3.MyID3.java

/**
 * Mengklasifikasikan instance//  www .  j av a 2s .c o m
 * @param instance data yang ingin di klasifikasikan
 * @return hasil klasifikasi
 * @throws NoSupportForMissingValuesException
 */
public double classifyInstance(Instance instance) throws NoSupportForMissingValuesException {
    if (instance.hasMissingValue()) {
        throw new NoSupportForMissingValuesException("Cannot handle missing value");
    }
    if (currentAttribute == null) {
        return classLabel;
    } else {
        return subTree[(int) instance.value(currentAttribute)].classifyInstance(instance);
    }
}

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From source file:id3.MyID3.java

/**
 * Menghitung pendistribusian class dalam instances
 * @param instance data yang ingin dihitung distribusinya
 * @return distribusi kelas dari instance
 * @throws NoSupportForMissingValuesException
 *///from w  ww  . jav a  2 s . c  om
public double[] distributionForInstance(Instance instance) throws NoSupportForMissingValuesException {
    if (instance.hasMissingValue()) {
        throw new NoSupportForMissingValuesException("Cannot handle missing value");
    }
    if (currentAttribute == null) {
        return classDistributionAmongInstances;
    } else {
        return subTree[(int) instance.value(currentAttribute)].distributionForInstance(instance);
    }
}

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From source file:myID3.MyId3.java

/**
* Classifies a given test instance using the decision tree.
*
* @param instance the instance to be classified
* @return the classification//from   w  w  w .j  a  va 2s  . com
* @throws NoSupportForMissingValuesException if instance has missing values
*/
public double classifyInstance(Instance instance) throws NoSupportForMissingValuesException {
    if (instance.hasMissingValue()) {
        throw new NoSupportForMissingValuesException("Id3: no missing values, " + "please.");
    }
    if (currentAttribute == null) {
        return classValue;
    } else {
        return nodes[(int) instance.value(currentAttribute)].classifyInstance(instance);
    }
}

---

From source file:myID3.MyId3.java

/**
 * Computes class distribution for instance using decision tree.
 *
 * @param instance the instance for which distribution is to be computed
 * @return the class distribution for the given instance
 * @throws NoSupportForMissingValuesException if instance has missing values
 *//*  w ww  . j a  v a  2 s. c o m*/
public double[] distributionForInstance(Instance instance) throws NoSupportForMissingValuesException {
    if (instance.hasMissingValue()) {
        throw new NoSupportForMissingValuesException("Id3: no missing values, " + "please.");
    }
    if (currentAttribute == null) {
        return classDistribution;
    } else {
        return nodes[(int) instance.value(currentAttribute)].distributionForInstance(instance);
    }
}

---

From source file:myid3andc45classifier.Model.MyID3.java

@Override
public double classifyInstance(Instance instance) throws NoSupportForMissingValuesException {

    //Periksa apakah instance memiliki missing value
    if (instance.hasMissingValue()) {
        throw new NoSupportForMissingValuesException("MyID3: no missing values, please");
    }/*from  w ww. ja va2s.  co  m*/

    if (attribute == null) {
        return label;
    } else {
        return successors[(int) instance.value(attribute)].classifyInstance(instance);
    }

}

---

From source file:myJ48.MyJ48.java

/**
 * Computes class distribution for instance using decision tree.
 *
 * @param instance the instance for which distribution is to be computed
 * @return the class distribution for the given instance
 * @throws NoSupportForMissingValuesException if instance has missing values
 */// www  .j  a v  a2s.com
public double[] distributionForInstance(Instance instance) throws NoSupportForMissingValuesException {
    if (instance.hasMissingValue()) {
        throw new NoSupportForMissingValuesException("Missing value error");
    }
    if (currentAttribute == null) {
        return classDistribution;
    } else {
        return nodes[(int) instance.value(currentAttribute)].distributionForInstance(instance);
    }
}

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From source file:newdtl.NewID3.java

/**
 * Classifies a given test instance using the decision tree.
 *
 * @param instance the instance to be classified
 * @return the classification/*w ww  .j  av  a 2 s . c o  m*/
 * @throws NoSupportForMissingValuesException if instance has missing values
 */
@Override
public double classifyInstance(Instance instance) throws NoSupportForMissingValuesException {

    if (instance.hasMissingValue()) {
        throw new NoSupportForMissingValuesException("NewID3: Cannot handle missing values");
    }
    if (splitAttribute == null) {
        return label;
    } else {
        return children[(int) instance.value(splitAttribute)].classifyInstance(instance);
    }
}

---

From source file:newdtl.NewID3.java

/**
 * Computes class distribution for instance using decision tree.
 *
 * @param instance the instance for which distribution is to be computed
 * @return the class distribution for the given instance
 * @throws NoSupportForMissingValuesException if instance has missing values
 *///from ww w.  j  a  va2  s .  c  om
@Override
public double[] distributionForInstance(Instance instance) throws NoSupportForMissingValuesException {

    if (instance.hasMissingValue()) {
        throw new NoSupportForMissingValuesException("NewID3: Cannot handle missing values");
    }
    if (splitAttribute == null) {
        return classDistributions;
    } else {
        return children[(int) instance.value(splitAttribute)].distributionForInstance(instance);
    }
}

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