About: Feature hashing

Facets (new session)
Description
Metadata
Settings
- Rule:
- Inverse Functional Properties:
- "Same As":

About: Feature hashing Goto Sponge NotDistinct Permalink

An Entity of Type : owl:Thing, within Data Space : dbpedia.org associated with source document(s)
QRcode icon

http://dbpedia.org/describe/?url=http%3A%2F%2Fdbpedia.org%2Fresource%2FFeature_hashing

In machine learning, feature hashing, also known as the hashing trick (by analogy to the kernel trick), is a fast and space-efficient way of vectorizing features, i.e. turning arbitrary features into indices in a vector or matrix. It works by applying a hash function to the features and using their hash values as indices directly, rather than looking the indices up in an associative array. This trick is often attributed to Weinberger et al. (2009), but there exists a much earlier description of this method published by John Moody in 1989.

Attributes	Values
rdfs:label	Feature hashing (en) Feature Hashing (ja)
rdfs:comment	In machine learning, feature hashing, also known as the hashing trick (by analogy to the kernel trick), is a fast and space-efficient way of vectorizing features, i.e. turning arbitrary features into indices in a vector or matrix. It works by applying a hash function to the features and using their hash values as indices directly, rather than looking the indices up in an associative array. This trick is often attributed to Weinberger et al. (2009), but there exists a much earlier description of this method published by John Moody in 1989. (en) 機械学習において、Feature Hashing（フィーチャーハッシング）は、高速かつ省メモリな特徴量をベクトルに変換する手法であり、任意の特徴をベクトルあるいは行列のインデックスに変換する。kernel trick(カーネルトリック)に似せてHashing Trick（ハッシュトリック）とも呼ばれる。連想配列を走査するのではなく、ハッシュ関数を特徴量に適用し、その値をインデックスとして直接使用する。 (ja)
name	Theorem (en)
dcterms:subject	Articles with example pseudocode Machine learning Hashing
Wikipage page ID	36126852 (xsd:integer)
Wikipage revision ID	1114513799 (xsd:integer)
Link from a Wikipage to another Wikipage	Scikit-learn Bloom filter Robert Burton Vowpal Wabbit Count–min sketch One-hot encoding Gensim Multi-task learning The Anatomy of Melancholy Apache Mahout Apache Spark Machine learning Complete metric space Zipf's law Feature (machine learning) Kernel method Articles with example pseudocode Machine learning Actual infinity Trie Document classification Hash function Heaps' law Linear model Locality-sensitive hashing Finite support Discrete metric Hashing Hash table Hilbert space TensorFlow Associative array Spam filter Sparse matrix Term-document matrix Inner product space MinHash R (programming language) Yahoo! Research Kleene star Kernel trick Type–token distinction Polysemy Bag of words
Link from a Wikipage to an external page	https://ml.dask.org/modules/generated/dask_ml.feature_extraction.text.HashingVectorizer.html%23dask_ml.feature_extraction.text.HashingVectorizer http://hunch.net/~jl/projects/hash_reps/index.html https://web.archive.org/web/20120609232923/http:/metaoptimize.com/qa/questions/6943/what-is-the-hashing-trick
sameAs	Feature hashing Feature hashing Feature hashing Feature hashing
dbp:wikiPageUsesTemplate	dbt:Blockquote dbt:Math dbt:Mono dbt:Mvar dbt:Reflist dbt:Proof dbt:Math_theorem
author	Robert Burton
proof	By linearity of expectation, Now, , since we assumed is unbiased. So we continue (en)
source	Part 2, Sect. II, Mem. IV. (en)
text	By this art you may contemplate the variation of the 23 letters... (en)
title	The Anatomy of Melancholy Proof (en)
has abstract	In machine learning, feature hashing, also known as the hashing trick (by analogy to the kernel trick), is a fast and space-efficient way of vectorizing features, i.e. turning arbitrary features into indices in a vector or matrix. It works by applying a hash function to the features and using their hash values as indices directly, rather than looking the indices up in an associative array. This trick is often attributed to Weinberger et al. (2009), but there exists a much earlier description of this method published by John Moody in 1989. (en) 機械学習において、Feature Hashing（フィーチャーハッシング）は、高速かつ省メモリな特徴量をベクトルに変換する手法であり、任意の特徴をベクトルあるいは行列のインデックスに変換する。kernel trick(カーネルトリック)に似せてHashing Trick（ハッシュトリック）とも呼ばれる。連想配列を走査するのではなく、ハッシュ関数を特徴量に適用し、その値をインデックスとして直接使用する。 (ja)
math statement	If the binary hash is unbiased , then is an isometry in expectation: (en)
prov:wasDerivedFrom	wikipedia-en:Feature_hashing?oldid=1114513799&ns=0
page length (characters) of wiki page	19896 (xsd:nonNegativeInteger)
foaf:isPrimaryTopicOf	wikipedia-en:Feature_hashing
is Link from a Wikipage to another Wikipage of	Bloom filter Vowpal Wabbit Count–min sketch Online machine learning Locality-sensitive hashing Count sketch Streaming algorithm Outline of machine learning Hash kernel Hash trick Hashing-Trick Hashing trick Hashtrick
is Wikipage redirect of	Hash kernel Hash trick Hashing-Trick Hashing trick Hashtrick
is foaf:primaryTopic of	wikipedia-en:Feature_hashing

Faceted Search & Find service v1.17_git139 as of Feb 29 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 08.03.3330 as of Mar 19 2024, on Linux (x86_64-generic-linux-glibc212), Single-Server Edition (61 GB total memory, 51 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software