Kedis ku xidhan hagaha · Dhexdhexaad Heerka

Kediska Kalasoocida Naive Bayes

Hubi sida Naive Bayes uu isugu daro horudhacyada fasalka iyo fursadaha muujinta, iyo sida ay kala duwanaansheedu u maamulaan tirinta, sifooyinka binary, iyo xogta joogtada ah.

Wadooyinka haga ee la xidhiidhaKalasaarayaasha Naive Bayes
Su'aal 1 ee 8

Waa maxay maloowga 'naive' ee asaasiga ah ee kala soocida Naive Bayes?

Horudhac su'aal kasta8 su'aalo

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

  1. Waa maxay maloowga 'naive' ee asaasiga ah ee kala soocida Naive Bayes?
    • Tilmaamuhu waa kuwo shuruudi ku xidhan yihiin marka la eego fasalka
    • Fasallada waa isku mid
    • Dhammaan sifooyinka waa kuwo joogto ah oo si caadi ah loo qaybiyo
    • Xogta xogta ayaa si fiican u dheelli tiran
  2. Aragtidee Naive Bayes lagu dhisay?
    • Aragtida xadka dhexe
    • Bayes’ theorem
    • Sharciga tirada badan
    • The Cauchy-Schwarz inequality
  3. Waa maxay sababta ay hawl-fulintu caadi ahaan isu geeyaan itimaalka-Log-ga halkii ay ku dhufan lahaayeen itimaalka cayriin?
    • Si aad moodelka uga dhigto mid aan toos ahayn
    • Si loo dedejiyo tababarka hal baas
    • Si looga fogaado qulqulka tirooyinka inuu badiyo tiro yar oo badan
    • Si loo dhaqan geliyo madaxbanaanida muuqaalka
  4. Dhibaato noocee ah ayuu xalliyaa Laplace (mid-mid) fududayntu?
    • Waxay dheellitiraysaa cabbirrada fasalka
    • Waxay caadi ka dhigtaa sifooyinka joogtada ah
    • Waxay meesha ka saartaa sifooyinka isku xidhan
    • Waxay ka hortagtaa sifada aan la arki karin inay qasabto itimaalka eber
  5. Kala duwanaanshiyaha Naive Bayes ee ugu dabiiciga ah sifada tirinta kelmad ee dukumentiyada?
    • Naive Bayes Multinomial
    • Gaussian Naive Bayes
    • Bernoulli Naive Bayes
    • Linear Naive Bayes
  6. Why might Naive Bayes be useful as a lightweight baseline?
    • Waxay dammaanad qaadaysaa saxnaanta ugu fiican ee xog kasta
    • Waa dhakhso, la tarjumi karaa, oo si fiican ugu shaqeeya xog yar
    • Waxay si toos ah u barataa isdhexgalka sifada
    • Uma baahna xog tababar
  7. What distribution does Gaussian Naive Bayes assume for each feature within a class?
    • A uniform distribution over every possible value
    • A multinomial distribution over word counts
    • A Gaussian (normal) distribution
    • A distribution that is always exactly zero
  8. Which feature representation fits Bernoulli Naive Bayes most naturally?
    • The number of times each word occurs
    • A continuous pixel intensity modeled by a normal curve
    • A sequence of audio frames
    • Whether each word is present or absent in a document