MISSING VALUE IMPUTATION USING ADAPTIVE ORDERING AND CLUSTERING ANALYSIS

MISSING VALUE IMPUTATION USING ADAPTIVE ORDERING AND CLUSTERING ANALYSIS

As received, a data value of an expected input set of received data values is missing from user input. A subset of known data with data values similar to a subset of the received data values is determined. A data sample average for the missing data value is determined from data values within the sub...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Lee, Sunhwan, Cao, Lingtao, Knoop, Sarah E
Format: Patent
Sprache:eng
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title
container_volume
creator Lee, Sunhwan
Cao, Lingtao
Knoop, Sarah E
description As received, a data value of an expected input set of received data values is missing from user input. A subset of known data with data values similar to a subset of the received data values is determined. A data sample average for the missing data value is determined from data values within the subset of the known data. An initial estimate of the missing data value is initialized using the data sample average. Boundary data clusters near the initial estimate of the missing data value are identified within the subset of the known data. A data harvesting region encapsulated according to the boundary clusters is defined. Data support clusters within at least one subset of the known data inside the data harvesting region are selected. The initial estimate of the missing data value is updated based upon data of the boundary clusters and the data support clusters.
format Patent
fullrecord <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US2019303471A1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US2019303471A1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US2019303471A13</originalsourceid><addsrcrecordid>eNrjZPDw9QwO9vRzVwhz9Al1VfD0DQgNcQzx9PdTCAULO7o4BoR4hrkq-Ae5uAaBRfxcFJx9QoNDYFxHn8hgz2AeBta0xJziVF4ozc2g7OYa4uyhm1qQH59aXJCYnJqXWhIfGmxkYGhpbGBsYm7oaGhMnCoA6tEuJQ</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>MISSING VALUE IMPUTATION USING ADAPTIVE ORDERING AND CLUSTERING ANALYSIS</title><source>esp@cenet</source><creator>Lee, Sunhwan ; Cao, Lingtao ; Knoop, Sarah E</creator><creatorcontrib>Lee, Sunhwan ; Cao, Lingtao ; Knoop, Sarah E</creatorcontrib><description>As received, a data value of an expected input set of received data values is missing from user input. A subset of known data with data values similar to a subset of the received data values is determined. A data sample average for the missing data value is determined from data values within the subset of the known data. An initial estimate of the missing data value is initialized using the data sample average. Boundary data clusters near the initial estimate of the missing data value are identified within the subset of the known data. A data harvesting region encapsulated according to the boundary clusters is defined. Data support clusters within at least one subset of the known data inside the data harvesting region are selected. The initial estimate of the missing data value is updated based upon data of the boundary clusters and the data support clusters.</description><language>eng</language><creationdate>2019</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20191003&amp;DB=EPODOC&amp;CC=US&amp;NR=2019303471A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20191003&amp;DB=EPODOC&amp;CC=US&amp;NR=2019303471A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Lee, Sunhwan</creatorcontrib><creatorcontrib>Cao, Lingtao</creatorcontrib><creatorcontrib>Knoop, Sarah E</creatorcontrib><title>MISSING VALUE IMPUTATION USING ADAPTIVE ORDERING AND CLUSTERING ANALYSIS</title><description>As received, a data value of an expected input set of received data values is missing from user input. A subset of known data with data values similar to a subset of the received data values is determined. A data sample average for the missing data value is determined from data values within the subset of the known data. An initial estimate of the missing data value is initialized using the data sample average. Boundary data clusters near the initial estimate of the missing data value are identified within the subset of the known data. A data harvesting region encapsulated according to the boundary clusters is defined. Data support clusters within at least one subset of the known data inside the data harvesting region are selected. The initial estimate of the missing data value is updated based upon data of the boundary clusters and the data support clusters.</description><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2019</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZPDw9QwO9vRzVwhz9Al1VfD0DQgNcQzx9PdTCAULO7o4BoR4hrkq-Ae5uAaBRfxcFJx9QoNDYFxHn8hgz2AeBta0xJziVF4ozc2g7OYa4uyhm1qQH59aXJCYnJqXWhIfGmxkYGhpbGBsYm7oaGhMnCoA6tEuJQ</recordid><startdate>20191003</startdate><enddate>20191003</enddate><creator>Lee, Sunhwan</creator><creator>Cao, Lingtao</creator><creator>Knoop, Sarah E</creator><scope>EVB</scope></search><sort><creationdate>20191003</creationdate><title>MISSING VALUE IMPUTATION USING ADAPTIVE ORDERING AND CLUSTERING ANALYSIS</title><author>Lee, Sunhwan ; Cao, Lingtao ; Knoop, Sarah E</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US2019303471A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2019</creationdate><toplevel>online_resources</toplevel><creatorcontrib>Lee, Sunhwan</creatorcontrib><creatorcontrib>Cao, Lingtao</creatorcontrib><creatorcontrib>Knoop, Sarah E</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Lee, Sunhwan</au><au>Cao, Lingtao</au><au>Knoop, Sarah E</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>MISSING VALUE IMPUTATION USING ADAPTIVE ORDERING AND CLUSTERING ANALYSIS</title><date>2019-10-03</date><risdate>2019</risdate><abstract>As received, a data value of an expected input set of received data values is missing from user input. A subset of known data with data values similar to a subset of the received data values is determined. A data sample average for the missing data value is determined from data values within the subset of the known data. An initial estimate of the missing data value is initialized using the data sample average. Boundary data clusters near the initial estimate of the missing data value are identified within the subset of the known data. A data harvesting region encapsulated according to the boundary clusters is defined. Data support clusters within at least one subset of the known data inside the data harvesting region are selected. The initial estimate of the missing data value is updated based upon data of the boundary clusters and the data support clusters.</abstract><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier
ispartof
issn
language eng
recordid cdi_epo_espacenet_US2019303471A1
source esp@cenet
title MISSING VALUE IMPUTATION USING ADAPTIVE ORDERING AND CLUSTERING ANALYSIS
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T15%3A37%3A07IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=Lee,%20Sunhwan&rft.date=2019-10-03&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EUS2019303471A1%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true