Esempio n. 1
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	/**
	 * @brief	Gets the cross differences between the training and test inputs.
	 * @param	[in] pXs		The M test inputs
	 * @param	[in] coord	Corresponding coordinate
	 * @return	An matrix pointer
	 *				\f[
	 *				\mathbf{D} \in \mathbb{R}^{N \times M}, \quad
	 *				\mathbf{D}_{ij} = \mathbf{x}_i^c - \mathbf{z}_j^c
	 *				\f]
	 * @todo		Include this matrix as a member variable like m_pDeltaXXList
	 */
	MatrixPtr pDeltaXXs(const TestData<Scalar> &testData, const int coord) const
	{
		assert(m_pX && testData.M() > 0);
		assert(D() == testData.D());
		return PairwiseOp<Scalar>::delta(m_pX, testData.pXs(), coord); // NxM
	}
Esempio n. 2
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	/**
	 * @brief	Gets the cross squared distances between the training and test inputs
	 * @param	[in] pXs		The M test inputs
	 * @return	An matrix pointer
	 *				\f[
	 *				\mathbf{R^2} \in \mathbb{R}^{N \times M}, \quad
	 *				\mathbf{R^2}_{ij} = (\mathbf{x}_i - \mathbf{z}_j)^\text{T}(\mathbf{x}_i - \mathbf{z}_j)
	 *				\f]
	 * @todo		Include this matrix as a member variable like m_pSqDistXX
	 */
	MatrixPtr pSqDistXXs(const TestData<Scalar> &testData) const
	{
		assert(m_pX && testData.M() > 0);
		assert(D() == testData.D());
		return PairwiseOp<Scalar>::sqDist(m_pX, testData.pXs()); // NxM
	}