本文整理了Java中weka.core.Instances.attributeStats()
方法的一些代码示例,展示了Instances.attributeStats()
的具体用法。这些代码示例主要来源于Github
/Stackoverflow
/Maven
等平台,是从一些精选项目中提取出来的代码,具有较强的参考意义,能在一定程度帮忙到你。Instances.attributeStats()
方法的具体详情如下:
包路径:weka.core.Instances
类名称:Instances
方法名:attributeStats
[英]Calculates summary statistics on the values that appear in this set of instances for a specified attribute.
[中]计算指定属性的此实例集中出现的值的摘要统计信息。
代码示例来源:origin: nz.ac.waikato.cms.weka/weka-stable
@Override
public void run() {
m_AttributeStats[index] = m_Instances.attributeStats(index);
SwingUtilities.invokeLater(new Runnable() {
@Override
public void run() {
setDerived(index);
m_StatsTable.sizeColumnsToFit(-1);
m_StatsTable.revalidate();
m_StatsTable.repaint();
}
});
}
};
代码示例来源:origin: Waikato/weka-trunk
@Override
public void run() {
m_AttributeStats[index] = m_Instances.attributeStats(index);
SwingUtilities.invokeLater(new Runnable() {
@Override
public void run() {
setDerived(index);
m_StatsTable.sizeColumnsToFit(-1);
m_StatsTable.revalidate();
m_StatsTable.repaint();
}
});
}
};
代码示例来源:origin: nz.ac.waikato.cms.weka/weka-stable
/**
* Tells the panel which attribute to visualize.
*
* @param index The index of the attribute
*/
public void setAttribute(int index) {
synchronized (m_locker) {
// m_threadRun = true;
m_threadRun = false;
m_doneCurrentAttribute = false;
m_displayCurrentAttribute = true;
// if(m_hc!=null && m_hc.isAlive()) m_hc.stop();
m_attribIndex = index;
if (m_asCache[index] != null) {
m_as = m_asCache[index];
} else {
m_asCache[index] = m_data.attributeStats(index);
m_as = m_asCache[index];
}
// m_as = m_data.attributeStats(m_attribIndex);
// m_classIndex = m_colorAttrib.getSelectedIndex();
}
this.repaint();
// calcGraph();
}
代码示例来源:origin: Waikato/weka-trunk
/**
* Tells the panel which attribute to visualize.
*
* @param index The index of the attribute
*/
public void setAttribute(int index) {
synchronized (m_locker) {
// m_threadRun = true;
m_threadRun = false;
m_doneCurrentAttribute = false;
m_displayCurrentAttribute = true;
// if(m_hc!=null && m_hc.isAlive()) m_hc.stop();
m_attribIndex = index;
if (m_asCache[index] != null) {
m_as = m_asCache[index];
} else {
m_asCache[index] = m_data.attributeStats(index);
m_as = m_asCache[index];
}
// m_as = m_data.attributeStats(m_attribIndex);
// m_classIndex = m_colorAttrib.getSelectedIndex();
}
this.repaint();
// calcGraph();
}
代码示例来源:origin: net.sf.meka.thirdparty/mulan
private void Initialize(MultiLabelInstances mlData) {
Instances dataSet = mlData.getDataSet();
int[] featureIndices = mlData.getFeatureIndices();
for (int attIndex : featureIndices) {
Attribute feature = dataSet.attribute(attIndex);
if (feature.isNumeric()) {
Stats stats = dataSet.attributeStats(attIndex).numericStats;
attStats.put(attIndex, new double[]{stats.min, stats.max});
}
}
}
}
代码示例来源:origin: nz.ac.waikato.cms.weka/weka-stable
stats = inst.attributeStats(attIdx);
if (m_Invert) {
count = stats.nominalCounts.length - m_NumValues;
stats = inst.attributeStats(attIdx);
for (i = 0; i < stats.nominalCounts.length; i++) {
if ((stats.nominalCounts[i] >= min) && (stats.nominalCounts[i] <= max)
代码示例来源:origin: nz.ac.waikato.cms.weka/weka-stable
/**
* checks the statistics of the attribute
*/
public void testStats() {
checkStatistics(
"MIN", m_Instances.attributeStats(m_AttIndex).numericStats.min);
checkStatistics(
"MAX", m_Instances.attributeStats(m_AttIndex).numericStats.max);
checkStatistics(
"MEAN", m_Instances.attributeStats(m_AttIndex).numericStats.mean);
checkStatistics(
"SD", m_Instances.attributeStats(m_AttIndex).numericStats.stdDev);
checkStatistics(
"COUNT", m_Instances.attributeStats(m_AttIndex).numericStats.count);
checkStatistics(
"SUM", m_Instances.attributeStats(m_AttIndex).numericStats.sum);
checkStatistics(
"SUMSQUARED", m_Instances.attributeStats(m_AttIndex).numericStats.sumSq);
}
代码示例来源:origin: Waikato/weka-trunk
/**
* checks the statistics of the attribute
*/
public void testStats() {
checkStatistics(
"MIN", m_Instances.attributeStats(m_AttIndex).numericStats.min);
checkStatistics(
"MAX", m_Instances.attributeStats(m_AttIndex).numericStats.max);
checkStatistics(
"MEAN", m_Instances.attributeStats(m_AttIndex).numericStats.mean);
checkStatistics(
"SD", m_Instances.attributeStats(m_AttIndex).numericStats.stdDev);
checkStatistics(
"COUNT", m_Instances.attributeStats(m_AttIndex).numericStats.count);
checkStatistics(
"SUM", m_Instances.attributeStats(m_AttIndex).numericStats.sum);
checkStatistics(
"SUMSQUARED", m_Instances.attributeStats(m_AttIndex).numericStats.sumSq);
}
代码示例来源:origin: Waikato/weka-trunk
AttributeStats as = instances.attributeStats(i);
if (m_upperBoundMinSupport == 1.0 && maxCount != numInstances) {
代码示例来源:origin: nz.ac.waikato.cms.weka/distributedWekaBase
AttributeStats as = inst.attributeStats(attIndex);
double pIndex = quantile * (inst.numInstances() - as.missingCount);
double mean = as.numericStats.mean;
代码示例来源:origin: nz.ac.waikato.cms.weka/weka-stable
/**
* Pretty hokey heuristic to try and set t2 distance automatically based on
* standard deviation
*
* @param trainingBatch the training instances
* @throws Exception if a problem occurs
*/
protected void setT2T1BasedOnStdDev(Instances trainingBatch) throws Exception {
double normalizedStdDevSum = 0;
for (int i = 0; i < trainingBatch.numAttributes(); i++) {
if (trainingBatch.attribute(i).isNominal()) {
normalizedStdDevSum += 0.25;
} else if (trainingBatch.attribute(i).isNumeric()) {
AttributeStats stats = trainingBatch.attributeStats(i);
if (trainingBatch.numInstances() - stats.missingCount > 2) {
double stdDev = stats.numericStats.stdDev;
double min = stats.numericStats.min;
double max = stats.numericStats.max;
if (!Utils.isMissingValue(stdDev) && max - min > 0) {
stdDev = 0.5 * stdDev / (max - min);
normalizedStdDevSum += stdDev;
}
}
}
}
normalizedStdDevSum = Math.sqrt(normalizedStdDevSum);
if (normalizedStdDevSum > 0) {
m_t2 = normalizedStdDevSum;
}
}
代码示例来源:origin: Waikato/weka-trunk
/**
* Pretty hokey heuristic to try and set t2 distance automatically based on
* standard deviation
*
* @param trainingBatch the training instances
* @throws Exception if a problem occurs
*/
protected void setT2T1BasedOnStdDev(Instances trainingBatch) throws Exception {
double normalizedStdDevSum = 0;
for (int i = 0; i < trainingBatch.numAttributes(); i++) {
if (trainingBatch.attribute(i).isNominal()) {
normalizedStdDevSum += 0.25;
} else if (trainingBatch.attribute(i).isNumeric()) {
AttributeStats stats = trainingBatch.attributeStats(i);
if (trainingBatch.numInstances() - stats.missingCount > 2) {
double stdDev = stats.numericStats.stdDev;
double min = stats.numericStats.min;
double max = stats.numericStats.max;
if (!Utils.isMissingValue(stdDev) && max - min > 0) {
stdDev = 0.5 * stdDev / (max - min);
normalizedStdDevSum += stdDev;
}
}
}
}
normalizedStdDevSum = Math.sqrt(normalizedStdDevSum);
if (normalizedStdDevSum > 0) {
m_t2 = normalizedStdDevSum;
}
}
代码示例来源:origin: nz.ac.waikato.cms.weka/weka-stable
private void testDistributionSpread_X(double factor) throws Exception {
AttributeStats origs = m_Instances.attributeStats(1);
assertNotNull(origs.nominalCounts);
((SpreadSubsample)m_Filter).setDistributionSpread(factor);
Instances result = useFilter();
assertEquals(m_Instances.numAttributes(), result.numAttributes());
AttributeStats outs = result.attributeStats(1);
// Check distributions are pretty similar
assertNotNull(outs.nominalCounts);
assertEquals(origs.nominalCounts.length, outs.nominalCounts.length);
int min = outs.nominalCounts[0];
int max = outs.nominalCounts[0];
for (int i = 1; i < outs.nominalCounts.length; i++) {
if (outs.nominalCounts[i] < min) {
min = outs.nominalCounts[i];
}
if (outs.nominalCounts[i] > max) {
max = outs.nominalCounts[i];
}
}
assertTrue(max / factor <= min);
}
代码示例来源:origin: nz.ac.waikato.cms.weka/weka-stable
public void testNoBias() throws Exception {
m_Instances.setClassIndex(1);
AttributeStats origs = m_Instances.attributeStats(1);
assertNotNull(origs.nominalCounts);
Instances result = useFilter();
assertEquals(m_Instances.numAttributes(), result.numAttributes());
AttributeStats outs = result.attributeStats(1);
// Check distributions are pretty similar
assertNotNull(outs.nominalCounts);
assertEquals(origs.nominalCounts.length, outs.nominalCounts.length);
for (int i = 0; i < origs.nominalCounts.length; i++) {
int est = origs.nominalCounts[i] / 2 - 1;
assertTrue("Counts for value:" + i
+ " orig:" + origs.nominalCounts[i]
+ " out50%:" + outs.nominalCounts[i],
(est <= outs.nominalCounts[i]) &&
(outs.nominalCounts[i] <= (est + 3)));
}
}
代码示例来源:origin: Waikato/weka-trunk
public void testNoBias() throws Exception {
m_Instances.setClassIndex(1);
AttributeStats origs = m_Instances.attributeStats(1);
assertNotNull(origs.nominalCounts);
Instances result = useFilter();
assertEquals(m_Instances.numAttributes(), result.numAttributes());
AttributeStats outs = result.attributeStats(1);
// Check distributions are pretty similar
assertNotNull(outs.nominalCounts);
assertEquals(origs.nominalCounts.length, outs.nominalCounts.length);
for (int i = 0; i < origs.nominalCounts.length; i++) {
int est = origs.nominalCounts[i] / 2 - 1;
assertTrue("Counts for value:" + i
+ " orig:" + origs.nominalCounts[i]
+ " out50%:" + outs.nominalCounts[i],
(est <= outs.nominalCounts[i]) &&
(outs.nominalCounts[i] <= (est + 3)));
}
}
代码示例来源:origin: Waikato/weka-trunk
private void testDistributionSpread_X(double factor) throws Exception {
AttributeStats origs = m_Instances.attributeStats(1);
assertNotNull(origs.nominalCounts);
((SpreadSubsample)m_Filter).setDistributionSpread(factor);
Instances result = useFilter();
assertEquals(m_Instances.numAttributes(), result.numAttributes());
AttributeStats outs = result.attributeStats(1);
// Check distributions are pretty similar
assertNotNull(outs.nominalCounts);
assertEquals(origs.nominalCounts.length, outs.nominalCounts.length);
int min = outs.nominalCounts[0];
int max = outs.nominalCounts[0];
for (int i = 1; i < outs.nominalCounts.length; i++) {
if (outs.nominalCounts[i] < min) {
min = outs.nominalCounts[i];
}
if (outs.nominalCounts[i] > max) {
max = outs.nominalCounts[i];
}
}
assertTrue(max / factor <= min);
}
代码示例来源:origin: Waikato/weka-trunk
public void testBiasToUniform() throws Exception {
m_Instances.setClassIndex(1);
AttributeStats origs = m_Instances.attributeStats(1);
assertNotNull(origs.nominalCounts);
((Resample)m_Filter).setBiasToUniformClass(1.0);
Instances result = useFilter();
assertEquals(m_Instances.numAttributes(), result.numAttributes());
AttributeStats outs = result.attributeStats(1);
// Check distributions are pretty similar
assertNotNull(outs.nominalCounts);
assertEquals(origs.nominalCounts.length, outs.nominalCounts.length);
int est = (origs.totalCount - origs.missingCount) / origs.distinctCount;
est = est / 2 - 1;
for (int i = 0; i < origs.nominalCounts.length; i++) {
assertTrue("Counts for value:" + i
+ " orig:" + origs.nominalCounts[i]
+ " out50%:" + outs.nominalCounts[i]
+ " ~wanted:" + est,
(est <= outs.nominalCounts[i]) &&
(outs.nominalCounts[i] <= (est + 3)));
}
}
代码示例来源:origin: nz.ac.waikato.cms.weka/weka-stable
public void testBiasToUniform() throws Exception {
m_Instances.setClassIndex(1);
AttributeStats origs = m_Instances.attributeStats(1);
assertNotNull(origs.nominalCounts);
((Resample)m_Filter).setBiasToUniformClass(1.0);
Instances result = useFilter();
assertEquals(m_Instances.numAttributes(), result.numAttributes());
AttributeStats outs = result.attributeStats(1);
// Check distributions are pretty similar
assertNotNull(outs.nominalCounts);
assertEquals(origs.nominalCounts.length, outs.nominalCounts.length);
int est = (origs.totalCount - origs.missingCount) / origs.distinctCount;
est = est / 2 - 1;
for (int i = 0; i < origs.nominalCounts.length; i++) {
assertTrue("Counts for value:" + i
+ " orig:" + origs.nominalCounts[i]
+ " out50%:" + outs.nominalCounts[i]
+ " ~wanted:" + est,
(est <= outs.nominalCounts[i]) &&
(outs.nominalCounts[i] <= (est + 3)));
}
}
代码示例来源:origin: nz.ac.waikato.cms.weka/weka-stable
continue; // skip class
AttributeStats stats = toFilter.attributeStats(i);
if (stats.missingCount == toFilter.numInstances()) {
attsToDelete[numToDelete++] = i;
代码示例来源:origin: nz.ac.waikato.cms.weka/distributedWekaBase
AttributeStats stats = denormalized.attributeStats(i);
if (denormalized.attribute(i).isNumeric()) {
NumericStats ns = new NumericStats(denormalized.attribute(i).name());
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