Autonomous training method and device of algorithm model, equipment and storage medium
The invention provides an autonomous training method and device of an algorithm model, equipment and a storage medium, and relates to the technical field of data processing. The method comprises the steps of determining whether to start a model training task according to parameters of a to-be-execut...
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creator | GUAN KAI FAN CHANGJIE LYU TANGJIE SHEN XUDONG SONG LINHAI XIAO ZHENMIN HU ZHIPENG |
description | The invention provides an autonomous training method and device of an algorithm model, equipment and a storage medium, and relates to the technical field of data processing. The method comprises the steps of determining whether to start a model training task according to parameters of a to-be-executed training task; if it is determined that the model training task is started, training a model corresponding to the to-be-executed training task based on a training data set to obtain a training index; judging according to the training index and a target parameter of the model, and determining whether an evaluation condition is met or not; and if the evaluation condition is reached, obtaining a trained target model. Compared with the prior art, the method avoids the problem that the algorithm model needs a lot of manual participation and is highly dependent on manual work.
本申请提供一种算法模型的自主训练方法、装置、设备及存储介质,涉及数据处理技术领域。该方法包括:根据待执行训练任务的参数,确定是否启动模型训练任务;若确定启动模型训练任务,则基于训练数据集对所述待执行训练任务对应的模型进行训练,获取训练指标;根据所述训练指标和所述模型的目标参数进行判断, |
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本申请提供一种算法模型的自主训练方法、装置、设备及存储介质,涉及数据处理技术领域。该方法包括:根据待执行训练任务的参数,确定是否启动模型训练任务;若确定启动模型训练任务,则基于训练数据集对所述待执行训练任务对应的模型进行训练,获取训练指标;根据所述训练指标和所述模型的目标参数进行判断,</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; PHYSICS</subject><creationdate>2023</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&date=20230711&DB=EPODOC&CC=CN&NR=116415148A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230711&DB=EPODOC&CC=CN&NR=116415148A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>GUAN KAI</creatorcontrib><creatorcontrib>FAN CHANGJIE</creatorcontrib><creatorcontrib>LYU TANGJIE</creatorcontrib><creatorcontrib>SHEN XUDONG</creatorcontrib><creatorcontrib>SONG LINHAI</creatorcontrib><creatorcontrib>XIAO ZHENMIN</creatorcontrib><creatorcontrib>HU ZHIPENG</creatorcontrib><title>Autonomous training method and device of algorithm model, equipment and storage medium</title><description>The invention provides an autonomous training method and device of an algorithm model, equipment and a storage medium, and relates to the technical field of data processing. The method comprises the steps of determining whether to start a model training task according to parameters of a to-be-executed training task; if it is determined that the model training task is started, training a model corresponding to the to-be-executed training task based on a training data set to obtain a training index; judging according to the training index and a target parameter of the model, and determining whether an evaluation condition is met or not; and if the evaluation condition is reached, obtaining a trained target model. Compared with the prior art, the method avoids the problem that the algorithm model needs a lot of manual participation and is highly dependent on manual work.
本申请提供一种算法模型的自主训练方法、装置、设备及存储介质,涉及数据处理技术领域。该方法包括:根据待执行训练任务的参数,确定是否启动模型训练任务;若确定启动模型训练任务,则基于训练数据集对所述待执行训练任务对应的模型进行训练,获取训练指标;根据所述训练指标和所述模型的目标参数进行判断,</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNy7EKwjAQgOEsDqK-w7nrEKzStRTFyUlcy9Fc00CSi8nF51fEB3D6l-9fqkdXhSMHrgUko4suWggkMxvAaMDQy40EPAF6y9nJHCCwIb8DelaXAkX5wiKc0dLnNa6GtVpM6Attfl2p7eV87697SjxQSThSJBn6m9anRh9103aHf8wbORM5rw</recordid><startdate>20230711</startdate><enddate>20230711</enddate><creator>GUAN KAI</creator><creator>FAN CHANGJIE</creator><creator>LYU TANGJIE</creator><creator>SHEN XUDONG</creator><creator>SONG LINHAI</creator><creator>XIAO ZHENMIN</creator><creator>HU ZHIPENG</creator><scope>EVB</scope></search><sort><creationdate>20230711</creationdate><title>Autonomous training method and device of algorithm model, equipment and storage medium</title><author>GUAN KAI ; FAN CHANGJIE ; LYU TANGJIE ; SHEN XUDONG ; SONG LINHAI ; XIAO ZHENMIN ; HU ZHIPENG</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN116415148A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2023</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>GUAN KAI</creatorcontrib><creatorcontrib>FAN CHANGJIE</creatorcontrib><creatorcontrib>LYU TANGJIE</creatorcontrib><creatorcontrib>SHEN XUDONG</creatorcontrib><creatorcontrib>SONG LINHAI</creatorcontrib><creatorcontrib>XIAO ZHENMIN</creatorcontrib><creatorcontrib>HU ZHIPENG</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>GUAN KAI</au><au>FAN CHANGJIE</au><au>LYU TANGJIE</au><au>SHEN XUDONG</au><au>SONG LINHAI</au><au>XIAO ZHENMIN</au><au>HU ZHIPENG</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Autonomous training method and device of algorithm model, equipment and storage medium</title><date>2023-07-11</date><risdate>2023</risdate><abstract>The invention provides an autonomous training method and device of an algorithm model, equipment and a storage medium, and relates to the technical field of data processing. The method comprises the steps of determining whether to start a model training task according to parameters of a to-be-executed training task; if it is determined that the model training task is started, training a model corresponding to the to-be-executed training task based on a training data set to obtain a training index; judging according to the training index and a target parameter of the model, and determining whether an evaluation condition is met or not; and if the evaluation condition is reached, obtaining a trained target model. Compared with the prior art, the method avoids the problem that the algorithm model needs a lot of manual participation and is highly dependent on manual work.
本申请提供一种算法模型的自主训练方法、装置、设备及存储介质,涉及数据处理技术领域。该方法包括:根据待执行训练任务的参数,确定是否启动模型训练任务;若确定启动模型训练任务,则基于训练数据集对所述待执行训练任务对应的模型进行训练,获取训练指标;根据所述训练指标和所述模型的目标参数进行判断,</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
title | Autonomous training method and device of algorithm model, equipment and storage medium |
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