private Similarity ComputeSimilarity(NamedVector <NamedValue> vector1, NamedVector <NamedValue> vector2,
Dictionary <string, double> averages)
{
var sharedUsers = vector1.Values.Join(vector2.Values,
nv => nv.Name,
nv => nv.Name,
(first, second) =>
new
{
Item1 = first.Value,
Item2 = second.Value,
UserAverage = averages[first.Name]
})
.ToList();
var numerator = sharedUsers.Sum(user => (user.Item1 - user.UserAverage) * (user.Item2 - user.UserAverage));
var root1 = sharedUsers.Sum(user => (user.Item1 - user.UserAverage).Square()).SquareRoot();
var root2 = sharedUsers.Sum(user => (user.Item2 - user.UserAverage).Square()).SquareRoot();
var denominator = root1 * root2;
var result = numerator / denominator;
return(new Similarity(vector1.Name, vector2.Name, result));
}
public Correlation ComputeCorrelation(NamedVector <NamedValue> vector1, NamedVector <NamedValue> vector2)
{
var jointValues = vector1.Values.Join(vector2.Values, nv => nv.Name, nv => nv.Name,
(f, s) => new { X = f.Value, Y = s.Value }).ToList();
// calculating numerator
var dotProduct = jointValues.Sum(p => p.X * p.Y);
var productOfSums = jointValues.Sum(p => p.X) * jointValues.Sum(p => p.Y);
var numerator = dotProduct - (productOfSums / jointValues.Count);
// calculating denominator
var squareOfSumX = jointValues.Sum(p => p.X).Square();
var magnitudeX = jointValues.Sum(p => p.X.Square());
var squareRoot1 = (magnitudeX - squareOfSumX / jointValues.Count).SquareRoot();
var squareOfSumY = jointValues.Sum(p => p.Y).Square();
var magnitudeY = jointValues.Sum(p => p.Y.Square());
var sqaureRoot2 = (magnitudeY - squareOfSumY / jointValues.Count).SquareRoot();
var denominator = squareRoot1 * sqaureRoot2;
// calculating result
var result = numerator / denominator;
return(new Similarity(vector1.Name, vector2.Name, result));
}
public Correlation ComputeCorrelation(NamedVector<NamedValue> vector1, NamedVector<NamedValue> vector2)
{
var jointValues = vector1.Values.Join(vector2.Values, nv => nv.Name, nv => nv.Name,
(f, s) => new { X = f.Value, Y = s.Value }).ToList();
var sum = jointValues.Sum(p => (p.X - p.X).ToAbsolute().ToPowerOf(_exponent));
var result = sum.RootOfDegree(_exponent);
return new Distance(vector1.Name, vector2.Name, result);
}
public Correlation ComputeCorrelation(NamedVector<NamedValue> vector1, NamedVector<NamedValue> vector2)
{
var jointValues = vector1.Values.Join(vector2.Values, nv => nv.Name, nv => nv.Name,
(f, s) => new { X = f.Value, Y = s.Value }).ToList();
var sum = jointValues.Sum(p => (p.X - p.X).ToAbsolute().ToPowerOf(_exponent));
var result = sum.RootOfDegree(_exponent);
return new Distance(vector1.Name, vector2.Name, result);
}
public Correlation ComputeCorrelation(NamedVector<NamedValue> vector1, NamedVector<NamedValue> vector2)
{
var jointValues = vector1.Values.Join(vector2.Values, nv => nv.Name, nv => nv.Name,
(f, s) => new {X = f.Value, Y = s.Value}).ToList();
var dotProduct = jointValues.Sum(p => p.X * p.Y);
var magnitudeX = jointValues.Sum(p => p.X.Square());
var magnitudeY = jointValues.Sum(p => p.Y.Square());
var denominator = magnitudeX.SquareRoot() * magnitudeY.SquareRoot();
var result = dotProduct/denominator;
return new Similarity(vector1.Name, vector2.Name, result);
}
public Correlation ComputeCorrelation(NamedVector <NamedValue> vector1, NamedVector <NamedValue> vector2)
{
var jointValues = vector1.Values.Join(vector2.Values, nv => nv.Name, nv => nv.Name,
(f, s) => new { X = f.Value, Y = s.Value }).ToList();
var dotProduct = jointValues.Sum(p => p.X * p.Y);
var magnitudeX = jointValues.Sum(p => p.X.Square());
var magnitudeY = jointValues.Sum(p => p.Y.Square());
var denominator = magnitudeX.SquareRoot() * magnitudeY.SquareRoot();
var result = dotProduct / denominator;
return(new Similarity(vector1.Name, vector2.Name, result));
}
private Tuple <string, string, double> ComputeDeviations(NamedVector <NamedValue> vector1, NamedVector <NamedValue> vector2)
{
var sharedUsers = vector1.Values.Join(vector2.Values,
nv => nv.Name,
nv => nv.Name,
(first, second) =>
new
{
First = first.Value,
Second = second.Value
})
.ToList();
var deviation = sharedUsers.Sum(obj => (obj.First - obj.Second) / sharedUsers.Count);
return(Tuple.Create(vector1.Name, vector2.Name, deviation));
}
