Garab yiy jël dogal ak àll yu bari
Garab giy jël dogal dafay wax luy waaja am ci laaj ay laaj yu yomb waaw/déedet, lu melni diagram.
Résumé
A random forest combines hundreds of such trees and lets them vote, which is far more accurate and robust.
Plongeur bu xóot
Garab dogal dafay xaaj done yi jéego ak jéego: ci node bu nekk dafay tànn màndarga ak threshold bi gëna mëna tàqale njariñ yi, ba noppi car yi ba muy yegg ci benn prediction ci benn xob. Trees are popular because they are easy to read; you can trace exactly why a decision was made. Seen ñakk kattan mooy overfitting, fu garab gu xóot gi di xam bruit bi te du mëna wax luy am ci done yu bees yi. Garab yu bari yi deñuy saafara jafe-jafe yi ci di tàggat garab yu bari ci ay done yu bari (pexem ñuy woowe sac) ak ay ensemble yu bari ci màndarga yi ci xaaj bu nekk. Garab yi dañuy def njuumte yu wuute, kon soo amee seeni wote ci diggante dafay fomm njuumte yi benn-benn nit def. Resultaa bi mooy benn ci algorithm yi gëna wóor, gëna néew tuning ngir done tabular, ñu bari ñu koy jëfandikoo balaa ñuy yegg ci njàng mu xóot.
Gis-gis xarala
Each split is chosen to maximize 'purity.' Garab yiy xaaj dañuy wàññi mbalit wala entropi bu Gini; garabi régression dañuy wàññi variance (njuumte kaare). Garab yu bari dañuy yokk ñaari balluwaay yu bari: bootstrap sampling (garab bu nekk dafay gis misaal buñ desine ak wuutu) ak tànneef ci anam wu bari ci xaaj bu nekk. Loolu dafay decorrelate garab yi suko defee seen prediction moyenne am variance bu gëna ndaw bu baax benn garab, te du yokk biais bu bari. Misali bi nekk ci bitti sac bi, ñu bàyyi ko ci bootstrap garab bu nekk, dafay joxe xayma buñ tabax ci biir.
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 garabi dogal ak àll yu bari
Garab yu bari yu amul benn yoon ñu ngi des ci yoon wi ñuy jaar, waaye limyéer bi dafa toxu ci garab yu am gradient yu melni XGBoost, LightGBM, ak CatBoost, ñu tabax garab yu toppalante ngir saafara njuumte yu njëkk ya, te dañuy faral di nekk ci kaw joŋante tabular. Ensemble garab yooyu ñu ngi wéy di gëna am doole ci reso neuronal yi ci done yu bari yuñ defar. Xaarandil liggéey buy wéy ci gaawaay, tàggat GPU, ak jumtukaayi leeral yu melni SHAP, ndax tekki mooy sabab bu mag bi liggéeyukaay yiñ yamale di wéy di tànn xeetu garab ci jàng bu xóot bu ñuul.
Doxal ci àdduna dëgg
Njortu leble ak nangu leble, fu bànk yi di xool yoonu dogal bu leer te ñu mëna saytu.
Xalaatal risku pajum dafay wane ban factëri malaad moo waral diagnostic bi wala àrtu bi.
Kiliyaan bi dafay wax luy waaja am ci kontu tablo ak done jëfandikoo.
Càmbaru njariñu màndarga ngir mëna tànn variable yi gëna am solo ci benn done.
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 garabi dogal ak garabi àll yu bari di jàppale ak fi pexe yu gëna yomba gëna baax.
Weyal di banneexu
Free newsletter
Get the daily AI briefing
Three verified AI stories every weekday morning, written in plain English. Free forever, no ads.
One email each weekday. Unsubscribe in one click. We never sell or share your address.
Test yourself
Take the Decision Trees and Random Forests quiz
Instant feedback on every answer, and a shareable certificate with a verifiable ID once you pass a course.
Support free AI education. AI Understanding is a 501(c)(3) nonprofit — no ads, no paywall, ever. Make a donation
Gis bi ci topp
Jël dogal ci IA
Laaj yi ñuy faral di laaj
What is Decision Trees and Random Forests?
Garab giy jël dogal dafay wax luy waaja am ci laaj ay laaj yu yomb waaw/déedet, lu melni diagram. Benn àll buñ tànn di boole téemeeri garab yu mel noonu, may leen ñu wote, te loolu moo gëna dëggu te gëna am doole.
Naka la garabu dogal di mëna wax luy am?
Garab dogal dafay yóbbu ay done ci ay laaj yu jëm ci ay màndargam ba keroog muy yegg ci xob buy joxe li ñuy wax.
Lan mooy ñakk kattan gu mag gi ci benn garabu dogal bu xóot?
Garab yu xóot yi mën nañu méngoo bu baax ak done yiñ tàggat, jàpp bruit bi ba noppi baña mëna yamale misaal yu bees yi.
naka lay demee ba garab gu bari gën?
Suñu tàggatee garab yu bari yu decorrelé ak moyenne wala wote, àll bi dafay fomm njuumti garab yi benn-benn ba noppi wàññi overfitting.
Luy 'sac' ci àll yu bari?
Bagging (agrégation bootstrap) dafay jox garab bu nekk benn misaal buñ jël ci anam wu bari, suko defee garab yi wuute, seen moyenne gëna dëgër.
Ban metric la garabi xaaj yi di faral di jëfandikoo ngir tànn xaaj bi?
Garab yiy xaaj dañuy tànn xaaj yi gëna wàññi Gini impurety wala entropy, di natt ni xaaj yi di jaxasoo ci benn node.