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📄 distribution.java

📁 weka 源代码很好的 对于学习 数据挖掘算法很有帮助
💻 JAVA
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    int counter = 0;    int i;    for (i=0;i<m_perBag.length;i++)      if (Utils.grOrEq(m_perBag[i],minNoObj))	counter++;    if (counter > 1)      return true;    else      return false;  }  /**   * Clones distribution (Deep copy of distribution).   */  public final Object clone() {    int i,j;    Distribution newDistribution = new Distribution (m_perBag.length,						     m_perClass.length);    for (i=0;i<m_perBag.length;i++) {      newDistribution.m_perBag[i] = m_perBag[i];      for (j=0;j<m_perClass.length;j++)	newDistribution.m_perClassPerBag[i][j] = m_perClassPerBag[i][j];    }    for (j=0;j<m_perClass.length;j++)      newDistribution.m_perClass[j] = m_perClass[j];    newDistribution.totaL = totaL;      return newDistribution;  }  /**   * Deletes given instance from given bag.   *   * @exception Exception if something goes wrong   */  public final void del(int bagIndex,Instance instance)        throws Exception {    int classIndex;    double weight;    classIndex = (int)instance.classValue();    weight = instance.weight();    m_perClassPerBag[bagIndex][classIndex] =       m_perClassPerBag[bagIndex][classIndex]-weight;    m_perBag[bagIndex] = m_perBag[bagIndex]-weight;    m_perClass[classIndex] = m_perClass[classIndex]-weight;    totaL = totaL-weight;  }  /**   * Deletes all instances in given range from given bag.   *   * @exception Exception if something goes wrong   */  public final void delRange(int bagIndex,Instances source,			     int startIndex, int lastPlusOne)       throws Exception {    double sumOfWeights = 0;    int classIndex;    Instance instance;    int i;    for (i = startIndex; i < lastPlusOne; i++) {      instance = (Instance) source.instance(i);      classIndex = (int)instance.classValue();      sumOfWeights = sumOfWeights+instance.weight();      m_perClassPerBag[bagIndex][classIndex] -= instance.weight();      m_perClass[classIndex] -= instance.weight();    }    m_perBag[bagIndex] -= sumOfWeights;    totaL -= sumOfWeights;  }  /**   * Prints distribution.   */    public final String dumpDistribution() {    StringBuffer text;    int i,j;    text = new StringBuffer();    for (i=0;i<m_perBag.length;i++) {      text.append("Bag num "+i+"\n");      for (j=0;j<m_perClass.length;j++)	text.append("Class num "+j+" "+m_perClassPerBag[i][j]+"\n");    }    return text.toString();  }  /**   * Sets all counts to zero.   */  public final void initialize() {    for (int i = 0; i < m_perClass.length; i++)       m_perClass[i] = 0;    for (int i = 0; i < m_perBag.length; i++)      m_perBag[i] = 0;    for (int i = 0; i < m_perBag.length; i++)      for (int j = 0; j < m_perClass.length; j++)	m_perClassPerBag[i][j] = 0;    totaL = 0;  }  /**   * Returns matrix with distribution of class values.   */  public final double[][] matrix() {    return m_perClassPerBag;  }    /**   * Returns index of bag containing maximum number of instances.   */  public final int maxBag() {    double max;    int maxIndex;    int i;        max = 0;    maxIndex = -1;    for (i=0;i<m_perBag.length;i++)      if (Utils.grOrEq(m_perBag[i],max)) {	max = m_perBag[i];	maxIndex = i;      }    return maxIndex;  }  /**   * Returns class with highest frequency over all bags.   */  public final int maxClass() {    double maxCount = 0;    int maxIndex = 0;    int i;    for (i=0;i<m_perClass.length;i++)      if (Utils.gr(m_perClass[i],maxCount)) {	maxCount = m_perClass[i];	maxIndex = i;      }    return maxIndex;  }  /**   * Returns class with highest frequency for given bag.   */  public final int maxClass(int index) {    double maxCount = 0;    int maxIndex = 0;    int i;    if (Utils.gr(m_perBag[index],0)) {      for (i=0;i<m_perClass.length;i++)	if (Utils.gr(m_perClassPerBag[index][i],maxCount)) {	  maxCount = m_perClassPerBag[index][i];	  maxIndex = i;	}      return maxIndex;    }else      return maxClass();  }  /**   * Returns number of bags.   */  public final int numBags() {        return m_perBag.length;  }  /**   * Returns number of classes.   */  public final int numClasses() {    return m_perClass.length;  }  /**   * Returns perClass(maxClass()).   */  public final double numCorrect() {    return m_perClass[maxClass()];  }  /**   * Returns perClassPerBag(index,maxClass(index)).   */  public final double numCorrect(int index) {    return m_perClassPerBag[index][maxClass(index)];  }  /**   * Returns total-numCorrect().   */  public final double numIncorrect() {    return totaL-numCorrect();  }  /**   * Returns perBag(index)-numCorrect(index).   */  public final double numIncorrect(int index) {    return m_perBag[index]-numCorrect(index);  }  /**   * Returns number of (possibly fractional) instances of given class in    * given bag.   */  public final double perClassPerBag(int bagIndex, int classIndex) {    return m_perClassPerBag[bagIndex][classIndex];  }  /**   * Returns number of (possibly fractional) instances in given bag.   */  public final double perBag(int bagIndex) {    return m_perBag[bagIndex];  }  /**   * Returns number of (possibly fractional) instances of given class.   */  public final double perClass(int classIndex) {    return m_perClass[classIndex];  }  /**   * Returns relative frequency of class over all bags with   * Laplace correction.   */  public final double laplaceProb(int classIndex) {    return (m_perClass[classIndex] + 1) /       (totaL + (double) actualNumClasses());  }  /**   * Returns relative frequency of class for given bag.   */  public final double laplaceProb(int classIndex, int intIndex) {    return (m_perClassPerBag[intIndex][classIndex] + 1.0) /      (m_perBag[intIndex] + (double) actualNumClasses());  }  /**   * Returns relative frequency of class over all bags.   */  public final double prob(int classIndex) {    if (!Utils.eq(totaL, 0)) {      return m_perClass[classIndex]/totaL;    } else {      return 0;    }  }  /**   * Returns relative frequency of class for given bag.   */  public final double prob(int classIndex,int intIndex) {    if (Utils.gr(m_perBag[intIndex],0))      return m_perClassPerBag[intIndex][classIndex]/m_perBag[intIndex];    else      return prob(classIndex);  }  /**    * Subtracts the given distribution from this one. The results   * has only one bag.   */  public final Distribution subtract(Distribution toSubstract) {    Distribution newDist = new Distribution(1,m_perClass.length);    newDist.m_perBag[0] = totaL-toSubstract.totaL;    newDist.totaL = newDist.m_perBag[0];    for (int i = 0; i < m_perClass.length; i++) {      newDist.m_perClassPerBag[0][i] = m_perClass[i] - toSubstract.m_perClass[i];      newDist.m_perClass[i] = newDist.m_perClassPerBag[0][i];    }    return newDist;  }  /**   * Returns total number of (possibly fractional) instances.   */  public final double total() {    return totaL;  }  /**   * Shifts given instance from one bag to another one.   *   * @exception Exception if something goes wrong   */  public final void shift(int from,int to,Instance instance)        throws Exception {        int classIndex;    double weight;    classIndex = (int)instance.classValue();    weight = instance.weight();    m_perClassPerBag[from][classIndex] -= weight;    m_perClassPerBag[to][classIndex] += weight;    m_perBag[from] -= weight;    m_perBag[to] += weight;  }  /**   * Shifts all instances in given range from one bag to another one.   *   * @exception Exception if something goes wrong   */  public final void shiftRange(int from,int to,Instances source,			       int startIndex,int lastPlusOne)        throws Exception {        int classIndex;    double weight;    Instance instance;    int i;    for (i = startIndex; i < lastPlusOne; i++) {      instance = (Instance) source.instance(i);      classIndex = (int)instance.classValue();      weight = instance.weight();      m_perClassPerBag[from][classIndex] -= weight;      m_perClassPerBag[to][classIndex] += weight;      m_perBag[from] -= weight;      m_perBag[to] += weight;    }  }}

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