| Class | Description | 
|---|---|
| EstimationUtils | |
| EstimatorBasicAvg | Basic average case estimator for matrix sparsity:
 sp = 1 - Math.pow(1-sp1*sp2, k) | 
| EstimatorBasicWorst | Basic average case estimator for matrix sparsity:
 sp = Math.min(1, sp1 * k) * Math.min(1, sp2 * k). | 
| EstimatorBitsetMM | This estimator implements a naive but rather common approach of boolean matrix
 multiplies which allows to infer the exact non-zero structure and thus is
 also useful for sparse result preallocation. | 
| EstimatorBitsetMM.BitsetMatrix | |
| EstimatorBitsetMM.BitsetMatrix1 | This class represents a boolean matrix and provides key operations. | 
| EstimatorBitsetMM.BitsetMatrix2 | |
| EstimatorDensityMap | This estimator implements an approach called density maps, as introduced in
 David Kernert, Frank Köhler, Wolfgang Lehner: SpMacho - Optimizing Sparse 
 Linear Algebra Expressions with Probabilistic Density Estimation. | 
| EstimatorDensityMap.DensityMap | |
| EstimatorLayeredGraph | This estimator implements an approach based on a so-called layered graph,
 introduced in
 Edith Cohen. | 
| EstimatorLayeredGraph.LayeredGraph | |
| EstimatorMatrixHistogram | This estimator implements a remarkably simple yet effective
 approach for incorporating structural properties into sparsity
 estimation. | 
| EstimatorMatrixHistogram.MatrixHistogram | |
| EstimatorSample | This estimator implements an approach based on row/column sampling
 Yongyang Yu, MingJie Tang, Walid G. | 
| EstimatorSampleRa | This estimator implements an approach based on row/column sampling
 
 Rasmus Resen Amossen, Andrea Campagna, Rasmus Pagh:
 Better Size Estimation for Sparse Matrix Products. | 
| MMNode | Helper class to represent matrix multiply operators in a DAG
 along with references to its abstract data handles. | 
| SparsityEstimator | 
| Enum | Description | 
|---|---|
| SparsityEstimator.OpCode | 
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