public void WriteFile(List <List <string> > numericDataset, string file, List <string> atrNames, List <string> targetValues, bool isTargetNumeric)
{
weka.core.FastVector targetVals = new weka.core.FastVector();
weka.core.Instances dataRel;
for (int i = 0; i < targetValues.Count; i++)
{
targetVals.addElement(targetValues[i]);
}
weka.core.Instances data;
weka.core.FastVector atts = new weka.core.FastVector();
// fill and prepare the dataset for the arrf file
for (int j = 0; j < insts.numAttributes(); j++)
{
if (j == insts.numAttributes() - 1 && isTargetNumeric == false) // target value can be nominal
{
atts.addElement(new weka.core.Attribute(atrNames[j], targetVals));
}
else
{
atts.addElement(new weka.core.Attribute(atrNames[j]));
}
}
data = new weka.core.Instances("MyRelation", atts, 0);
for (int i = 0; i < insts.numInstances(); i++)
{
double[] vals = new double[insts.numAttributes()];
for (int j = 0; j < insts.numAttributes(); j++)
{
if (j == insts.numAttributes() - 1 && isTargetNumeric == false) // target value can be nominal
{
vals[j] = targetVals.indexOf(numericDataset[j][i]);
}
else
{
vals[j] = Convert.ToDouble(numericDataset[j][i]);
}
}
data.add(new weka.core.DenseInstance(1.0, vals));
}
if (File.Exists(file))
{
File.Delete(file);
}
var saver = new weka.core.converters.ArffSaver();
saver.setInstances(data);
saver.setFile(new java.io.File(file));
// files are saved into {AppFolder}/bin/Debug folder. You can find two files in this path.
saver.writeBatch();
}
public void CSV2Arff()
{
//load csv
weka.core.converters.CSVLoader loader = new weka.core.converters.CSVLoader();
//weka.core.converters.TextDirectoryLoader loader = new weka.core.converters.TextDirectoryLoader();
// C:/ Users / DELL / source / repos / WekafromCtest / WekafromCtest /
loader.setSource(new java.io.File("D:/final_version/Gesture-Gis-master/GestureGis2/ComparisonFeaturefile.txt"));
weka.core.Instances data = loader.getDataSet();
//save arff
weka.core.converters.ArffSaver saver = new weka.core.converters.ArffSaver();
saver.setInstances(data);
//and save as arff file
saver.setFile(new java.io.File("D:/final_version/Gesture-Gis-master/GestureGis2/ComparisonFeaturefile.arff"));
saver.writeBatch();
}
protected void Button1_Click(object sender, EventArgs e)
{
try
{
string path = Server.MapPath(".") + "\\datasets\\" + dataset.Text + ".csv";
string fname = path;
File.Delete("d:\\train.arff");
weka.core.converters.CSVLoader loader = new weka.core.converters.CSVLoader();
loader.setSource(new java.io.File(fname));
weka.core.Instances inst2 = loader.getDataSet();
weka.core.converters.ArffSaver saver = new weka.core.converters.ArffSaver();
saver.setInstances(inst2);
saver.setFile(new java.io.File("d:\\train.arff"));
saver.writeBatch();
// Response.Write("<html><script>alert('File Converted..');</script></html>");
}
catch (Exception ex)
{
/// Response.Write("<html><script>alert('" + ex.Message.ToString() + "');</script></html>");
}
// weka.core.Instances data = new weka.core.Instances(new java.io.FileReader("d:\\train.arff"));
// data.setClassIndex(data.numAttributes() - 1);
// weka.classifiers.Classifier cls = new weka.classifiers.bayes.NaiveBayes();
//// weka.classifiers.functions.supportVector.SMOset();
// int runs = 1;
// int folds = 10;
// //string sq = "delete from nbresults";
// //dbc.execfn(sq);
// // perform cross-validation
// for (int i = 0; i < runs; i++)
// {
// // randomize data
// int seed = i + 1;
// java.util.Random rand = new java.util.Random(seed);
// weka.core.Instances randData = new weka.core.Instances(data);
// randData.randomize(rand);
// if (randData.classAttribute().isNominal())
// randData.stratify(folds);
// weka.classifiers.Evaluation eval = new weka.classifiers.Evaluation(randData);
// for (int n = 0; n < folds; n++)
// {
// weka.core.Instances train = randData.trainCV(folds, n);
// weka.core.Instances test = randData.testCV(folds, n);
// // build and evaluate classifier
// weka.classifiers.Classifier clsCopy = weka.classifiers.Classifier.makeCopy(cls);
// clsCopy.buildClassifier(train);
// eval.evaluateModel(clsCopy, test);
// }
// preci_value.Text = eval.precision(0).ToString();
// recall_value.Text = eval.recall(0).ToString();
// acc_value.Text = eval.fMeasure(0).ToString();
// string s = "NB";
// string str = "insert into evaluation values('" + instid.Text + "','" + courid.Text.ToString() + "','" + preci_value.Text.ToString() + "','" + recall_value.Text.ToString() + "','" + acc_value.Text.ToString() + "','"+ s+ "' )";
// dbc.execfn(str);
// MessageBox.Show("saved");
// }
// }
}
