Example usage for weka.core Instance hasMissingValue

Introduction

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

Prototype

public boolean hasMissingValue();

Source Link

Document

Tests whether an instance has a missing value.

Usage

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   www  .ja  v  a2 s  . c  om

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

}

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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
 *//*from  ww w  .  j  a v  a  2  s .c  o m*/
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);
    }
}

---

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  w w  .  j  ava2 s .c  om*/
 * @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
 *//*ww  w  .  j  av a  2  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);
    }
}

---

From source file:newdtl.NewJ48.java

/**
 * Classifies a given test instance using the decision tree.
 *
 * @param instance the instance to be classified
 * @return the classification/*from w w  w.  jav a2 s.  c o m*/
 */
@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 {
        if (splitAttribute.isNumeric()) {
            if (Double.compare(instance.value(splitAttribute), splitThreshold) <= 0) {
                return children[0].classifyInstance(instance);
            } else {
                return children[1].classifyInstance(instance);
            }
        } else {
            return children[(int) instance.value(splitAttribute)].classifyInstance(instance);
        }
    }
}

---

From source file:newdtl.NewJ48.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
 *//*w  w  w  .ja  v  a 2 s. c o m*/
@Override
public double[] distributionForInstance(Instance instance) throws NoSupportForMissingValuesException {
    if (instance.hasMissingValue()) {
        throw new NoSupportForMissingValuesException("NewID3: Cannot handle missing values");
    }

    if (splitAttribute == null) {
        return normalize(classDistributions);
    } else {
        if (splitAttribute.isNumeric()) {
            if (Double.compare(instance.value(splitAttribute), splitThreshold) <= 0) {
                return children[0].distributionForInstance(instance);
            } else {
                return children[1].distributionForInstance(instance);
            }
        } else {
            return children[(int) instance.value(splitAttribute)].distributionForInstance(instance);
        }
    }
}

---

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