/** * @param v The vector to compute the distance to * @return Mahalanobis distance of a multivariate vector */ public double distance(Vector v) { return Math.sqrt(v.minus(meanVector).dot(Algebra.mult(inverseCovarianceMatrix, v.minus(meanVector)))); }
/** * @param v The vector to compute the distance to * @return Mahalanobis distance of a multivariate vector */ public double distance(Vector v) { return Math.sqrt(v.minus(meanVector).dot(Algebra.mult(inverseCovarianceMatrix, v.minus(meanVector)))); }
/** * @param v The vector to compute the distance to * @return Mahalanobis distance of a multivariate vector */ public double distance(Vector v) { return Math.sqrt(v.minus(meanVector).dot(Algebra.mult(inverseCovarianceMatrix, v.minus(meanVector)))); }
@Override public double distance(Vector v1, Vector v2) { if (v1.size() != v2.size()) { throw new CardinalityException(v1.size(), v2.size()); } return Math.sqrt(v1.minus(v2).dot(Algebra.mult(inverseCovarianceMatrix, v1.minus(v2)))); }
@Override public double distance(Vector v1, Vector v2) { if (v1.size() != v2.size()) { throw new CardinalityException(v1.size(), v2.size()); } return Math.sqrt(v1.minus(v2).dot(Algebra.mult(inverseCovarianceMatrix, v1.minus(v2)))); }
@Override public double distance(Vector v1, Vector v2) { if (v1.size() != v2.size()) { throw new CardinalityException(v1.size(), v2.size()); } return Math.sqrt(v1.minus(v2).dot(Algebra.mult(inverseCovarianceMatrix, v1.minus(v2)))); }