## Uses of Class
org.apache.sysds.hops.estim.SparsityEstimator

- Packages that use SparsityEstimator
  Package | Description
  --- | ---
  org.apache.sysds.hops.estim |

- - ### Uses of SparsityEstimator in org.apache.sysds.hops.estim

    Subclasses of SparsityEstimator in org.apache.sysds.hops.estim
    Modifier and Type | Class and Description
    --- | ---
    `class` | `EstimatorBasicAvg` Basic average case estimator for matrix sparsity: sp = 1 - Math.pow(1-sp1*sp2, k)
    `class` | `EstimatorBasicWorst` Basic average case estimator for matrix sparsity: sp = Math.min(1, sp1 * k) * Math.min(1, sp2 * k).
    `class` | `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.
    `class` | `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.
    `class` | `EstimatorLayeredGraph` This estimator implements an approach based on a so-called layered graph, introduced in Edith Cohen.
    `class` | `EstimatorMatrixHistogram` This estimator implements a remarkably simple yet effective approach for incorporating structural properties into sparsity estimation.
    `class` | `EstimatorSample` This estimator implements an approach based on row/column sampling Yongyang Yu, MingJie Tang, Walid G.
    `class` | `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.

Copyright © 2020 The Apache Software Foundation. All rights reserved.