public void TestSimilarity()
{
var instance = new Jaccard(k: 2);
// AB BC CD DE DF
// 1 1 1 1 0
// 1 1 1 0 1
// => 3 / 5 = 0.6
var result = instance.Similarity("ABCDE", "ABCDF");
Assert.Equal(expected: 0.6, actual: result);
}
///// <summary>
///// Calcualtes the Levenshtein distance between two strings
///// </summary>
///// Source: https://en.wikibooks.org/wiki/Algorithm_Implementation/Strings/Levenshtein_distance#C.23
///// Explanation: https://en.wikipedia.org/wiki/Levenshtein_distance
//private Int32 levenshtein(String a, String b)
//{
// if (string.IsNullOrEmpty(a))
// {
// if (!string.IsNullOrEmpty(b))
// {
// return b.Length;
// }
// return 0;
// }
// if (string.IsNullOrEmpty(b))
// {
// if (!string.IsNullOrEmpty(a))
// {
// return a.Length;
// }
// return 0;
// }
// Int32 cost;
// Int32[,] d = new int[a.Length + 1, b.Length + 1];
// Int32 min1;
// Int32 min2;
// Int32 min3;
// for (Int32 i = 0; i <= d.GetUpperBound(0); i += 1)
// {
// d[i, 0] = i;
// }
// for (Int32 i = 0; i <= d.GetUpperBound(1); i += 1)
// {
// d[0, i] = i;
// }
// for (Int32 i = 1; i <= d.GetUpperBound(0); i += 1)
// {
// for (Int32 j = 1; j <= d.GetUpperBound(1); j += 1)
// {
// cost = Convert.ToInt32(!(a[i - 1] == b[j - 1]));
// min1 = d[i - 1, j] + 1;
// min2 = d[i, j - 1] + 1;
// min3 = d[i - 1, j - 1] + cost;
// d[i, j] = Math.Min(Math.Min(min1, min2), min3);
// }
// }
// return d[d.GetUpperBound(0), d.GetUpperBound(1)];
//}
///// <summary>
///// String-similarity computed with levenshtein-distance
///// </summary>
//private double similarityLevenshtein(string a, string b)
//{
// if (a.Equals(b))
// {
// return 1.0;
// }
// else
// {
// if (!(a.Length == 0 || b.Length == 0))
// {
// double sim = 1 - (levenshtein(a, b) / Convert.ToDouble(Math.Min(a.Length, b.Length)));
// return sim;
// }
// else
// return 0.0;
// }
//}
///// <summary>
///// String-similarity computed with Dice Coefficient
///// </summary>
///// Source: https://en.wikibooks.org/wiki/Algorithm_Implementation/Strings/Dice%27s_coefficient#C.23
///// Explanation: https://en.wikipedia.org/wiki/S%C3%B8rensen%E2%80%93Dice_coefficient
//private double similarityDiceCoefficient(string a, string b)
//{
// //Workaround for |a| == |b| == 1
// if (a.Length <= 1 && b.Length <= 1)
// {
// if (a.Equals(b))
// return 1.0;
// else
// return 0.0;
// }
// HashSet<string> setA = new HashSet<string>();
// HashSet<string> setB = new HashSet<string>();
// for (int i = 0; i < a.Length - 1; ++i)
// setA.Add(a.Substring(i, 2));
// for (int i = 0; i < b.Length - 1; ++i)
// setB.Add(b.Substring(i, 2));
// HashSet<string> intersection = new HashSet<string>(setA);
// intersection.IntersectWith(setB);
// return (2.0 * intersection.Count) / (setA.Count + setB.Count);
//}
/// <summary>
/// Combines multiple String-similarities with equal weight
/// </summary>
private double similarity(string a, string b)
{
List <double> similarities = new List <double>();
double output = 0.0;
var l = new NormalizedLevenshtein();
similarities.Add(l.Similarity(a, b));
var jw = new JaroWinkler();
similarities.Add(jw.Similarity(a, b));
var jac = new Jaccard();
similarities.Add(jac.Similarity(a, b));
foreach (double sim in similarities)
{
output += sim;
}
return(output / similarities.Count);
}
public static double GetSimilarityAverage(string str1, string str2)
{
return((cosine.Similarity(str1, str2) + jaccard.Similarity(str1, str2) + sorensenDice.Similarity(str1, str2)) / 3);
}
private void Ok_Click(object sender, RoutedEventArgs e)
{
var format = new NumberFormatInfo();
format.NegativeSign = "-";
var valuesCol1 = (from row in mainWindow.gridData.AsEnumerable()
select Convert.ToDouble(ConvertString(row.Field <string>(mainWindow.gridData.Columns[comboBoxCol1.SelectedItem.ToString()].ColumnName)), format)).ToArray();
var valuesCol2 = (from row in mainWindow.gridData.AsEnumerable()
select Convert.ToDouble(ConvertString(row.Field <string>(mainWindow.gridData.Columns[comboBoxCol2.SelectedItem.ToString()].ColumnName)), format)).ToArray();
if (similarityMeasures.SelectedItem.ToString() == "Jaccard")
{
var jaccard = new Jaccard();
textBlock.Text += "\nPodobieństwo miary Jaccard pomiędzy kolumnami " + comboBoxCol1.SelectedItem.ToString() + " i " + comboBoxCol2.SelectedItem.ToString() + " wynosi: " + jaccard.Similarity(valuesCol1, valuesCol2).ToString();
}
else if (similarityMeasures.SelectedItem.ToString() == "Korelacja Pearsona")
{
var pearsonCorrelation = new PearsonCorrelation();
textBlock.Text += "\nPodobieństwo miary Korelacja Pearsona pomiędzy kolumnami " + comboBoxCol1.SelectedItem.ToString() + " i " + comboBoxCol2.SelectedItem.ToString() + " wynosi: " + pearsonCorrelation.Similarity(valuesCol1, valuesCol2).ToString();
}
else if (similarityMeasures.SelectedItem.ToString() == "Cosinus")
{
var cosine = new Cosine();
textBlock.Text += "\nPodobieństwo miary Cosinus pomiędzy kolumnami " + comboBoxCol1.SelectedItem.ToString() + " i " + comboBoxCol2.SelectedItem.ToString() + " wynosi: " + cosine.Similarity(valuesCol1, valuesCol2).ToString();
}
}
