private EMModel generateEMModel(
EMModel trainModel,
List<String> newTransformColumns,
int clusterNumber,
ArrayList<Double> tempResult) {
trainModel.setClusterNumber(clusterNumber);
for (int i = 0; i < clusterNumber; i++) {
EMClusterNode tempNode = new EMClusterNode();
tempNode.setAlpha(tempResult.get(i));
Map<String, Double> muValue = new LinkedHashMap<String, Double>();
Map<String, Double> sigmaValue = new LinkedHashMap<String, Double>();
for (int j = 0; j < newTransformColumns.size(); j++) {
muValue.put(
newTransformColumns.get(j),
tempResult.get(clusterNumber + i * newTransformColumns.size() + j));
sigmaValue.put(
newTransformColumns.get(j),
tempResult.get(
clusterNumber
+ clusterNumber * newTransformColumns.size()
+ i * newTransformColumns.size()
+ j));
}
tempNode.setMuValue(muValue);
tempNode.setSigmaValue(sigmaValue);
trainModel.addClusteSingleValue(i + 1, tempNode);
}
return trainModel;
}
/* (non-Javadoc)
* @see com.alpine.datamining.api.impl.db.AbstractDBModelTrainer#train(com.alpine.datamining.api.AnalyticSource)
*/
@Override
protected Model train(AnalyticSource source) throws AnalysisException {
ResultSet rs = null;
Statement st = null;
EMModel trainModel = null;
try {
IDataSourceInfo dataSourceInfo =
DataSourceInfoFactory.createConnectionInfo(source.getDataSourceType());
dbtype = dataSourceInfo.getDBType();
EMConfig config = (EMConfig) source.getAnalyticConfig();
String anaColumns = config.getColumnNames();
String[] columnsArray = anaColumns.split(",");
List<String> transformColumns = new ArrayList<String>();
for (int i = 0; i < columnsArray.length; i++) {
transformColumns.add(columnsArray[i]);
}
DataSet dataSet = getDataSet((DataBaseAnalyticSource) source, config);
filerColumens(dataSet, transformColumns);
dataSet.computeAllColumnStatistics();
ColumnTypeTransformer transformer = new ColumnTypeTransformer();
DataSet newDataSet = transformer.TransformCategoryToNumeric_new(dataSet);
String tableName = ((DBTable) newDataSet.getDBTable()).getTableName();
Columns columns = newDataSet.getColumns();
List<String> newTransformColumns = new ArrayList<String>();
HashMap<String, String> transformMap = new HashMap<String, String>();
for (String key : transformer.getAllTransformMap_valueKey().keySet()) {
HashMap<String, String> values = (transformer.getAllTransformMap_valueKey()).get(key);
for (String lowKey : values.keySet()) {
transformMap.put(values.get(lowKey), lowKey);
}
}
Iterator<Column> attributeIter = columns.iterator();
while (attributeIter.hasNext()) {
Column column = attributeIter.next();
newTransformColumns.add(column.getName());
}
int maxIterationNumber = Integer.parseInt(config.getMaxIterationNumber());
int clusterNumber = Integer.parseInt(config.getClusterNumber());
double epsilon = Double.parseDouble(config.getEpsilon());
int initClusterSize = 10;
if (config.getInitClusterSize() != null) {
initClusterSize = Integer.parseInt(config.getInitClusterSize());
}
if (newDataSet.size() < initClusterSize * clusterNumber) {
initClusterSize = (int) (newDataSet.size() / clusterNumber + 1);
} // TODO get it from config and make sure it will not be too large
EMClusterImpl emImpl = EMClusterFactory.createEMAnalyzer(dbtype);
trainModel = EMClusterFactory.createEMModel(dbtype, newDataSet);
Connection connection = null;
connection = ((DataBaseAnalyticSource) source).getConnection();
st = connection.createStatement();
ArrayList<Double> tempResult =
emImpl.emTrain(
connection,
st,
tableName,
maxIterationNumber,
epsilon,
clusterNumber,
newTransformColumns,
initClusterSize,
trainModel);
trainModel = generateEMModel(trainModel, newTransformColumns, clusterNumber, tempResult);
if (!newDataSet.equals(this.dataSet)) {
trainModel.setAllTransformMap_valueKey(transformMap);
}
} catch (Exception e) {
logger.error(e);
if (e instanceof WrongUsedException) {
throw new AnalysisError(this, (WrongUsedException) e);
} else if (e instanceof AnalysisError) {
throw (AnalysisError) e;
} else {
throw new AnalysisException(e);
}
} finally {
try {
if (st != null) {
st.close();
}
if (rs != null) {
rs.close();
}
} catch (SQLException e) {
logger.debug(e.toString());
throw new AnalysisException(e.getLocalizedMessage());
}
}
return trainModel;
}