Hais tias, lawv tuaj yeem kwv yees qhov kev ua haujlwm tsis tu ncua arbitrarily ze. Piv txwv li, qhov kev ua haujlwm hnyav, uas yog 0 rau x=0 tuaj yeem kwv yees los ntawm sigmoid (lambdax) thiab qhov kwv yees tau zoo dua li lambda mus rau infinity.
Neural networks puas tuaj yeem kawm cov haujlwm tsis tu ncua?
Ib txheej peb txheej neural tuaj yeem sawv cev ib yam tsis txuas ntxiv ntau yam ua haujlwm. … Hauv daim ntawv no peb ua pov thawj tias tsis yog tsuas yog kev ua haujlwm tas mus li xwb tab sis kuj tseem muaj tag nrho cov haujlwm tsis tu ncua tuaj yeem siv tau los ntawm cov tes hauj lwm neural.
Puas yog lub network neural kwv yees ib qho haujlwm?
The Universal Approximation Theorem hais tias neural network nrog 1 txheej zais tuaj yeem kwv yees ib qho kev ua haujlwm tsis tu ncua rau cov khoom siv hauv ib qho tshwj xeeb. Yog tias txoj haujlwm dhia ncig lossis muaj qhov khoob loj, peb yuav tsis tuaj yeem kwv yees nws.
Neural network twg tuaj yeem kwv yees ua haujlwm txuas ntxiv?
Summing up, ib tug meej meej ntawm lub universality theorem yog hais tias neural tes hauj lwm nrog ib tug zais txheejtuaj yeem siv los kwv yees txhua qhov kev ua haujlwm tas mus li rau qhov xav tau.
Neural networks puas daws tau teeb meem?
Hnub no, neural networks tau siv rau daws ntau yam teeb meem kev lag luamxws li kev kwv yees muag, kev tshawb fawb cov neeg siv khoom, kev lees paub cov ntaub ntawv, thiab kev tswj hwm kev pheej hmoo. Piv txwv li, ntawm Statsbot pebsiv neural tes hauj lwm rau lub sij hawm-series kev kwv yees, kev tshawb nrhiav tsis pom hauv cov ntaub ntawv, thiab kev nkag siab hom lus.
