{"id":35384,"date":"2022-04-20T18:44:51","date_gmt":"2022-04-20T18:44:51","guid":{"rendered":""},"modified":"-0001-11-30T00:00:00","modified_gmt":"-0001-11-30T00:00:00","slug":"kuidas-kasutada-masinopet-spordiennustustes","status":"publish","type":"post","link":"https:\/\/amszterdam.com\/index.php\/2022\/04\/20\/kuidas-kasutada-masinopet-spordiennustustes\/","title":{"rendered":"Kuidas kasutada masin\u00f5pet spordiennustustes"},"content":{"rendered":"<h2>Traditsioonilised ennustused on vanaaegsed<\/h2>\n<p>V\u00e4lja\u00fctlemised ja \u201eintuition\u201c ei suuda enam konkureerida algoritmide t\u00e4psusega. Siin on peamine probleem: inimese aju on piiratud, andmevoog on l\u00f5pmatu. P\u00f5hjus on ilmne \u2013 masin\u00f5pe suudab korraga skaneerida miljonid statistikad, mis on inimajule k\u00e4ttesaamatud. Lase sellel masinatel n\u00e4idata, kus on t\u00f5eline v\u00e4\u00e4rtus. <\/p>\n<h2>Kuidas alustada<\/h2>\n<p>Vaata, mis on sinu andmemudel. Alustuseks vali spordiala, mille kohta on avatud andmebaasid \u2013 n\u00e4iteks jalgpall, tennise v\u00f5i korvpalli m\u00e4nguvahetused. Seej\u00e4rel loo struktureeritud CSV, mis kannab m\u00e4ngijaid, v\u00f5itu, haakeid, lahingu ajalehti. Siin tuleb olla pragmatiline, mitte kunstnik. Andmed peavad olema puhtad, muidu mudel \u00f5pib vale mustri.<\/p>\n<h3>V\u00f5ta algusandmeid kokku<\/h3>\n<p>Kasuta avatud API-sid, n\u00e4iteks <a href=\"https:\/\/spordiennustuskrupto.com\">spordiennustuskrupto.com<\/a>. Allalaaditud faili ei tohi pelgalt olla massiivne tekstifail \u2013 struktureeri need veerud, mis on mudeli jaoks m\u00f5istlikud: koduv\u00f5id, k\u00fclmk\u00e4ik, eeldatav l\u00f6\u00f6giarv. Andmed puhastatakse k\u00e4sitsi, sest masin \u00f5pib ka rumalaid ebaolulisi detaile.<\/p>\n<h3>Vali \u00f5ige algoritm<\/h3>\n<p>Siin on m\u00e4ng: logistiline regressioon annab kiire \u00fclevaate, aga Random Forest v\u00f5i XGBoost on need t\u00f6\u00f6riistad, mis t\u00f5stavad t\u00e4psuse 70\u201180% tasemele. \u00c4rge oodake, et \u00fcks kiht oleks piisav \u2013 mitmekihiline mudel on alati paremini varustatud, kui kahtluse korral.<\/p>\n<h2>Treeningprotsess: Kood ja kontroll<\/h2>\n<p>Kirjutage Pythonis skript, mis loeb CSV, jagab andmed treening\u2011 ja testkomplektiks 80\/20 reegli alusel, ja k\u00e4ivitab valitud mudeli. \u00c4rge unustage cross\u2011validation, see hoiab \u00fcle\u00f5ppimist eemal. H\u00fcpotees: mudel, mis suudab ennustada 70% tulemustest, on juba m\u00e4ngija, kellega tasub m\u00e4ngida.<\/p>\n<p>Siin on detail: funktsioon loss\u2011metric peaks olema kombineeritud, n\u00e4iteks log loss + F1\u2011skoor, et v\u00f5tta arvesse nii klassi tasakaalu kui ka eksitusi. J\u00e4lgi \u00f5ppimise k\u00f5veraid graafikuna, sest j\u00e4rsku k\u00f5ikumine t\u00e4hendab andmete rikkumist.<\/p>\n<h2>\u00c4ra lase masinal teha l\u00f5plikku otsust<\/h2>\n<p>Masin annab sulle skoorid \u2013 0,6 v\u00f5i 0,8 t\u00f5en\u00e4osus. Sinu \u00fclesanne on t\u00f5lgendada neid turgude kontekstis. Kasuta staking strateegiat: kui mudel pakub k\u00f5rgemat t\u00f5en\u00e4osust kui kodulehe marginaal, siis panusta. Kui t\u00f5en\u00e4osus on l\u00e4hedal 0,5\u2011le, siis v\u00f5ta tagasi. Jooksvad anal\u00fc\u00fcsid ja live\u2011ajastatud andmed annavad t\u00e4iendava kihi.<\/p>\n<h2>Viimased n\u00fcansid<\/h2>\n<p>J\u00e4lgi mudeli drift\u2019i. Kui n\u00e4dalas muudatused statistikas muudavad mudeli t\u00e4psuse, retraini. Automatiseeritud pipeline, mis kasutab Dockerit ja CI\/CD, hoiab sind alati samal lainel. \u00c4ra lase end h\u00e4irida v\u00e4ikestest v\u00e4ljakutsetest \u2013 masin \u00f5pib, kui andmed on puhtad ja t\u00f6\u00f6voog on j\u00e4rjekindel.<\/p>\n<p>Siin on kiire tegevus: v\u00f5ta oma esimene andmekogus, puhasta, jooksuta Random Forest, ja alusta panustamist kohe, kui mudel annab \u00fcle 0,75 t\u00f5en\u00e4osuse v\u00f5iduks. <\/p>\n","protected":false},"excerpt":{"rendered":"<p>Traditsioonilised ennustused on vanaaegsed V\u00e4lja\u00fctlemised ja \u201eintuition\u201c ei suuda enam konkureerida algoritmide t\u00e4psusega. Siin on peamine probleem: inimese aju on piiratud, andmevoog on l\u00f5pmatu. P\u00f5hjus on ilmne \u2013 masin\u00f5pe suudab korraga skaneerida miljonid statistikad, mis on inimajule k\u00e4ttesaamatud. Lase sellel masinatel n\u00e4idata, kus on t\u00f5eline v\u00e4\u00e4rtus. Kuidas alustada Vaata, mis on sinu andmemudel. Alustuseks vali [&hellip;]<\/p>\n","protected":false},"author":61,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"footnotes":""},"categories":[],"tags":[],"class_list":["post-35384","post","type-post","status-publish","format-standard","hentry"],"_links":{"self":[{"href":"https:\/\/amszterdam.com\/index.php\/wp-json\/wp\/v2\/posts\/35384","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/amszterdam.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/amszterdam.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/amszterdam.com\/index.php\/wp-json\/wp\/v2\/users\/61"}],"replies":[{"embeddable":true,"href":"https:\/\/amszterdam.com\/index.php\/wp-json\/wp\/v2\/comments?post=35384"}],"version-history":[{"count":0,"href":"https:\/\/amszterdam.com\/index.php\/wp-json\/wp\/v2\/posts\/35384\/revisions"}],"wp:attachment":[{"href":"https:\/\/amszterdam.com\/index.php\/wp-json\/wp\/v2\/media?parent=35384"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/amszterdam.com\/index.php\/wp-json\/wp\/v2\/categories?post=35384"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/amszterdam.com\/index.php\/wp-json\/wp\/v2\/tags?post=35384"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}