\returns the number of non zero coefficients */

\returns the number of nonzero pivots in the LU decomposition. * Here nonzero is meant in the exact sense, not in a fuzzy sense. * So that

\returns the outer stride */

\returns the block index where outer belongs to */

the permutation used in the QR factorization */

r""" Returns the time-independent part of hazard function, i.e. :math:`\exp(X\beta)` on given data. Parameters ------

r""" Predict on given data. Parameters ---------- X : array-like, shape(n_samples, p_features) Sample mat

r""" Prediction of the mean of each response on given data. Parameters ---------- X : array-like, shape(n_samples, p_

r""" Return the most possible class for given data. Parameters ---------- X : array-like, shape(n_samples, p_features

r""" Predict survival function. The survival function for an individual with feature vector :math:`x` is defined as .

Visual studio doesn't implement a rand_r() function since its implementation of rand() is already thread safe

Visual studio doesn't implement a rand_r() function since its implementation of rand() is already thread safe

Return a single random number, ranging from -0.5 to 0.5

\returns the rank of the matrix of which *this is the LU decomposition. * * \note This method has to determine which pivots should be cons

r""" Give new data, and it returns the explained ratio. Parameters ---------- X : array-like, shape (n_samples, n_fea

* \brief Allocate the internal array of pointers to blocks and their inner indices * * \note For fixed-size blocks, call setBlockSize() to

Forwards the resizing request to the nested expression * \sa DenseBase::resize(Index) */

Resize the matrix without preserving the data (the matrix is set to zero) */

* Return the location in \em rowvaluePtr() which starts each column */

\returns the number of rows */

Return the number of rows of the underlying matrix.

Return the number of rows of the underlying matrix.

Return the number of rows of the underlying matrix.

Returns the number of rows of the underlying matrix.

Return the number of rows of the underlying matrix.

Return the number of rows of the underlying matrix.

Return the number of rows of the underlying matrix.

Return the number of rows of the underlying matrix.

Return the number of rows of the underlying matrix.

Return the number of rows of the underlying matrix.

Return the number of rows of the underlying matrix.

r""" Give new data, and it returns the prediction accuracy. Parameters ---------- X : array-like, shape(n_samples, p_

r""" Give data, and it returns C-index. Parameters ---------- X : array-like, shape(n_samples, p_features)

r""" Give new data, and it returns the :math:`D^2` score. Parameters ---------- X : array-like, shape(n_samples, p_fe

r""" Give data, and it returns the coefficient of determination. Parameters ---------- X : array-like, shape(n_sample

r""" Give new data, and it returns the prediction error. Parameters ---------- X : array-like, shape(n_samples, p_fea

Give new data, and it returns normalized discounted cumulative gain. Parameters ---------- X : array-like, shape(n_s

Sets this matrix to be the identity matrix of the current size. */

Removes all non zeros but keep allocated memory * * This function does not free the currently allocated memory. To release as much as memo

\returns the signed distance between the plane \c *this and a point \a p. * \sa absDistance() */

create a reference spline */

Does nothing: provided for compatibility with SparseMatrix */