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- Dictionarysparse/spɑːs/
adjective
- 1. thinly dispersed or scattered: "areas of sparse population"
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Apr 13, 2024 · Thinly populated or having few items. The sparse shelves in the store indicated a supply issue. Meager; limited in quantity or number. Resources were sparse in the war-torn region. Spread out or distributed over a large area. Wildlife in the national park is sparse but diverse. Not thickly or densely grown or settled.
Mar 18, 2024 · Sparse data are those with many gaps. The term typically refers to a dataset in which the variables with actually useful data are rare. For instance, suppose we have a dataset of readings from six rain gauges over a period of time.
Sep 12, 2023 · A matrix is a two-dimensional data object having m rows and n columns, therefore a total of m*n values. If most of the values of a matrix are 0 then we say that the matrix is sparse. Consider a definition of Sparse where a matrix is considered sparse if the number of 0s is more than half of the elements in the matrix, Examples: Input ...
Mar 18, 2024 · In this tutorial, we’ll study the difference between sparse and dense graphs in graph theory. We’ll first start by discussing the concepts of size and order in a graph, from which we’ll derive a definition of graph density.
Dec 20, 2023 · Indexing methods in a database management system (DBMS) can be classified as dense or sparse indexing methods, depending on the number of index entries in the database. Let’s take a look at the differences between the two types of indexing methods: Types of index. Dense indexing and Sparse indexing are types of primary indexing.
Nov 7, 2023 · There are four types of indexing: Primary, Secondary Clustering, and Multivalued Indexing. Primary indexing is divided into two types, dense and sparse. Dense indexing is used when the index table contains records for every search key. Sparse indexing is used when the index table does not use a search key for every record.
Oct 2, 2023 · Sparse Data. Definition: Sparse data is a data representation where most of the values are zero or empty. In other words, only a small percentage of the data points carry non-zero values. Pros: Memory Efficiency: Sparse data consumes significantly less memory since it doesn’t store zero values.
Mar 18, 2024 · Sparse Layers. Sparse layers, on the other hand, have a smaller number of parameters than dense layers. This is because each neuron only interacts with a subset of the neurons in the previous layer, which reduces the number of connections between neurons.
Apr 17, 2024 · sparse \ spɑrs \ adjective. : not dense; few and scattered. Listen to the pronunciation. Powered by Vocabulary.com. The word sparse has appeared in 194 articles on NYTimes.com in the past...
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Aug 1, 2023 · Introduction. “Principal component analysis (PCA) is probably the most popular multivariate statistical technique and it is used by almost all scientific disciplines. It is also likely to be the oldest multivariate technique.” (Abdi & Williams, 2010 , p.433).
