protected double cacluateGroupRSquare(
DataSet dataSet,
String tableName,
String labelName,
LinearRegressionModelDB model,
String groupValue,
StringBuilder sb_notNull)
throws OperatorException {
// String notnull=sb_notNull.toString().substring(beginIndex, endIndex);
// notnull.replace("where", " and ");
double RSquare = 0.0;
StringBuffer RSquareSQL = new StringBuffer();
StringBuffer avgSQL = new StringBuffer();
avgSQL
.append(" select avg(")
.append(labelName)
.append(") from ")
.append(tableName)
.append(sb_notNull)
.append(" and ")
.append(StringHandler.doubleQ(groupbyColumn))
.append("=")
.append(StringHandler.singleQ(groupValue));
double avg = 0.0;
try {
itsLogger.debug(classLogInfo + ".cacluateRSquare():sql=" + avgSQL);
ResultSet rs = st.executeQuery(avgSQL.toString());
if (rs.next()) {
avg = rs.getDouble(1);
}
} catch (SQLException e) {
itsLogger.error(e.getMessage(), e);
return Double.NaN;
}
StringBuffer predictedValueSQL = new StringBuffer();
predictedValueSQL.append(model.generatePredictedString(dataSet));
RSquareSQL.append("select 1 - sum((")
.append(predictedValueSQL)
.append("-")
.append(labelName)
.append(")*(")
.append(predictedValueSQL)
.append("-")
.append(labelName)
.append("))*1.0/sum((")
.append(labelName)
.append("-(")
.append(avg)
.append("))*(")
.append(labelName)
.append("-(")
.append(avg)
.append("))) from ")
.append(tableName)
.append(sb_notNull)
.append(" and ")
.append(StringHandler.doubleQ(groupbyColumn))
.append("=")
.append(StringHandler.singleQ(groupValue));
try {
itsLogger.debug("LinearRegressionImpPGGP.cacluateRSquare():sql=" + RSquareSQL);
ResultSet rs = st.executeQuery(RSquareSQL.toString());
if (rs.next()) {
RSquare = rs.getDouble(1);
}
} catch (SQLException e) {
itsLogger.error(e.getMessage(), e);
return Double.NaN;
}
return RSquare;
}
protected void getCoefficientAndR2Group(
String columNames,
DataSet dataSet,
String labelName,
String tableName,
String newTableName,
Columns atts,
String[] columnNames,
StringBuilder sb_notNull)
throws OperatorException {
Iterator<Column> atts_i;
StringBuffer columnNamesArray = new StringBuffer();
columnNamesArray.append("array[1.0,");
atts_i = atts.iterator();
int i = 0;
while (atts_i.hasNext()) {
Column att = atts_i.next();
if (i != 0) {
columnNamesArray.append(",");
}
columnNamesArray.append(StringHandler.doubleQ(att.getName())).append("::float");
i++;
}
columnNamesArray.append("]");
String sql = null;
sql =
"select alpine_miner_mregr_coef("
+ labelName
+ "::float,"
+ columnNamesArray
+ ") , "
+ StringHandler.doubleQ(groupbyColumn)
+ " from "
+ newTableName
+ sb_notNull
+ " group by "
+ StringHandler.doubleQ(groupbyColumn);
itsLogger.debug(classLogInfo + ".getCoefficientAndR2():sql=" + sql);
HashMap<String, Matrix> XY = new HashMap<String, Matrix>();
try {
Object[] object = null;
ResultSet rs = st.executeQuery(sql.toString());
while (rs.next()) {
Matrix tempXY = new Matrix(columnNames.length + 1, 1);
Matrix tempHessian = new Matrix(columnNames.length + 1, columnNames.length + 1);
String groupValue = rs.getString(2);
object = (Object[]) rs.getArray(1).getArray();
for (int x = 0; x < columnNames.length + 1; x++) {
int y = x + 1;
double doubleValue = 0.0;
if (object[y] != null) {
if (object[y] instanceof BigDecimal) {
doubleValue = ((BigDecimal) object[y]).doubleValue();
} else if (object[y] instanceof Double) {
doubleValue = ((Double) object[y]).doubleValue();
} else if (object[y] instanceof Integer) {
doubleValue = ((Integer) object[y]).doubleValue();
} else {
doubleValue = ((Number) object[y]).doubleValue();
}
}
tempXY.set(x, 0, doubleValue);
}
XY.put(groupValue, tempXY);
double[] arrayarrayResult =
getHessian(
object,
columnNames.length + 2,
(columnNames.length + 1)
* (columnNames.length + 2)
/ 2); // new double[sbAllArray.size()];
i = 0;
for (int x = 0; x < columnNames.length + 1; x++) {
for (int y = x; y < columnNames.length + 1; y++) {
{
double h = 0.0;
if (!Double.isNaN(arrayarrayResult[i])) {
h = arrayarrayResult[i];
}
tempHessian.set(x, y, h);
if (x != y) {
tempHessian.set(y, x, h);
}
i++;
}
}
}
hessian.put(groupValue, tempHessian);
}
} catch (SQLException e) {
itsLogger.error(e.getMessage(), e);
throw new OperatorException(e.getLocalizedMessage());
}
boolean first = true;
for (String tempString : hessian.keySet()) {
Matrix beta = null;
Matrix varianceCovarianceMatrix = null;
Double[] tempCoefficients = new Double[columnNames.length + 1];
for (i = 0; i < tempCoefficients.length; i++) {
tempCoefficients[i] = 0.0;
}
try {
varianceCovarianceMatrix = hessian.get(tempString).SVDInverse();
beta = varianceCovarianceMatrix.times(XY.get(tempString));
for (i = 0; i < beta.getRowDimension(); i++) {
if (i == 0) {
tempCoefficients[beta.getRowDimension() - 1] = beta.get(i, 0);
} else {
tempCoefficients[i - 1] = beta.get(i, 0);
}
}
coefficients.put(tempString, tempCoefficients);
double r2 = 0;
getGroupCoefficientMap(columnNames, tempString);
if (first == true) {
model =
new LinearRegressionGroupGPModel(
dataSet,
columnNames,
columNames,
tempCoefficients,
coefficientmap.get(tempString));
first = false;
}
LinearRegressionModelDB tempModel =
new LinearRegressionModelDB(
dataSet, columnNames, columNames, tempCoefficients, coefficientmap.get(tempString));
if (!this.newDataSet.equals(this.dataSet)) {
tempModel.setAllTransformMap_valueKey(transformer.getAllTransformMap_valueKey());
}
tempModel.setInteractionColumnExpMap(transformer.getInteractionColumnExpMap());
tempModel.setInteractionColumnColumnMap(transformer.getInteractionColumnColumnMap());
r2 = cacluateGroupRSquare(dataSet, tableName, labelName, tempModel, tempString, sb_notNull);
tempModel.setR2(r2);
model.addOneModel(tempModel, tempString);
} catch (Exception e) {
itsLogger.error(e.getMessage(), e);
}
}
}
