Siggil bu jaar yoon
Cross-validation pexem resampling la ngir xayma ni model bi di mëna yamale ay done yuñu gisul.
Résumé
It makes better use of limited data and gives a more reliable performance estimate than a single train/test split.
Plongeur bu xóot
Benn saxaar/test split lu yomba dagg la: poñ yi nga am mingi aju ci rang yi nga wàcci ci test bi. Validaasioŋ croix dafay saafara lii ci wëlbati rôlu ensemble test bi. Ci k-fold cross-validation, dangay xaaj done yi ci k fold yu tolloo, tàggat ci k-1 ci ñoom, jàngat ci fold biñ tëye, ba noppi baamtu k yoon suko defee liiñ bu nekk ñu natt ko benn yoon ndànk. Moyenne k poñ yi dafay joxe xayma bu gëna dëgër boole ci nattug coppite. Tanneef yiñ gëna xam ñooy 5 wala 10 yoon. Variante yi bokkunaci k-fold buñ xaaj (baña bàyyi xeetu klaas yi ngir done yu tolloowul), bàyyi-benn-ci biti (k mingi méngoo ak limu misaal yi), ak xaaj-seriiru waxtu yu musul tàggat ci ëlëg ngir wax lu weesu.
Gis-gis xarala
Taxawam jaar-jaar moo gëna am doole ci tànneefi model ak tuning hyperparametre: dangay méngale configurations yi ci seeni poñ validaasioŋ moyen moo gën ñu boole leen ci benn xaaj. Benn fiir bu am solo mooy fuite done - bépp preprocessing bu 'gis' dataset bi yépp (scaling, tànneef man-man, imputation) dafa wara nekk ci biir fold bu nekk, te baña xaaj, wala sa xayma dina nekk lu jaarul yoon. Validaasioŋ buñ boole dafay tàqale tuning bi ak jàngat bu mujj bi ngir moytu senn bii.
njeextalu pexe
dogal yu gëna leer
Daf lay jàppale nga tàqale kàddu yu leer ci wàllu xarala ak làkku fësal njaay.
Njëgg ak budget
Mën nga laaj laaj yu gëna baax ci samp gi balaa ngay dugal xaalis wala sa jotu liggéey.
Ekip ak def liggéey
Ekip yi bokk xam-xam ñoo gëna mëna jël yenn dogal ci wàllu produit, politik ak jàng.
Ëlëgu gëm-gëmu cross-validation
Lu ensemble done yi ak model yi di màgg, def k cycles de formation yu mat dafay seer lool, moo tax praktiseur yi dañuy gëna bëgg benn ensemble validation bu mag buñ tëye ngir jàng bu xóot, fekk ñuy denc cross-validation ngir ensemble done yu ndaw wala tabular. ML otomatik ak jumtukaay yu melni GridSearchCV bu scikit-learn ak Optuna dañuy lakk jaar-jaar ci seetlu hiperparametre ci default. Gëstu baa ngi wéy ci xayma yu gëna yomb, gasoduc yu baña senn, ak gëmloo bu jaar yoon ngir done yuñ boole, hierarchique, ak yu aju ci waxtu.
Doxal ci àdduna dëgg
Jëfandikoo 5-yoon cross-validation ngir méngale régression logistik, àll bu bari, ak yokk degrade balaa ngay jël benn model.
Jëfandikoo stratifié k-fold ci kaw ab done bu desekilibre ngir gis njuuj njaaj suko defee fold bu nekk di tëye lu tollu ci benn xeetu rare-class.
Doxal GridSearchCV wala RandomizedSearchCV, ñuy saytu bépp boole hyperparametre ngir tànn jekkal yi gëna baax.
Jëfandikoo ay sérii waxtu (rolling/chaining forward) ngir jàngat ab stock wala ab forecast buy laaj te doo tàggat ci done yu ëlëg.
Risk yi ak balustrade yi
Ekip yu bari mën nañu jëfandikoo benn baat ci anam wu wuute, kon teela leeral yaatuwaayam.
Benchmark yi mën nañu nuru lu am doole waaye performance yi ci àdduna bi duñu tolloo.
Bëgg kalite done ak palaŋu jàngat dafay faral di jur njariñ yu yomba dagg.
Roadmap ngir samp gi
Tàmbaleel ci joxe leeral ci làkk wu leer ci njariñ li nga soxla.
Tannal benn metric bu baax ak benn anam bu baaxul balaa ngay saytu.
Doxal ab pilote bu ndaw ak ay done yu representatif, du ab demo bu leer.
Bindal fi Cross-Validation di jàppale ak fi pexe yu gëna yomba gëna baax.
Weyal di banneexu
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What is Cross-Validation?
Cross-validation pexem resampling la ngir xayma ni model bi di mëna yamale ay done yuñu gisul. Dafay gëna jëfandikoo ay done yu néew, ba noppi di joxe xayma performance bu gëna wóor, moo gën benn saxaar/test split.
Ci k-fold cross-validation buñ miin, ñaata yoon lañuy jëfandikoo poñ done bu nekk ngir saytu?
Pli bu nekk dafay nekk test set benn yoon ci k rond yi, kon echantillon bu nekk ñu ngi koy test benn yoon ba noppi ñu tàggat ko ci yeneen yi.
Lan mooy njariñ li gëna mag ci k-fold cross-validation ci benn xaaj saxaar/test?
Suñu defee moyenne ci kaw ay yoon yu bari, validation croix dafay wàññi variance bi ci xayma performance bi buñu ko méngale ak wéeru ci benn xaaj buñ tànn.
Lan moo waral k-fold cross-validation bu jaar yoon jaarul yoon ngir seetlu série temps?
Jaxas ay done yuñ komànde ci waxtu dafay dugal ëlëg ci tàggat, moo tax CV-serie yi dañuy jëfandikoo xaaj yu jëm kanam yuy tàggat ci seetlu yu weesu.