Uncertainty in AI: Conditional Independence & Bayes Rule

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  • เผยแพร่เมื่อ 15 ธ.ค. 2024

ความคิดเห็น • 10

  • @shreyashachoudhary480
    @shreyashachoudhary480 2 ปีที่แล้ว +1

    Clear and simple, thanks.

  • @shashankramesh702
    @shashankramesh702 ปีที่แล้ว +3

    How does p(catch,toothache,cavity) have 7 entries.... why is he subtracting that 1 ?
    He did something similar to say he reduced 32 to 10 instead of 12 by subtracting 1 from p(catch,toothache,cavity) and 1 from p(weather). What exactly does he mean by parameters ?

    • @felicsmoses1771
      @felicsmoses1771 ปีที่แล้ว +8

      Sum of all probabilities is 1. So if we know 7 parameters, the last one is simply 1 minus the sum of seven.

  • @nayananandvats2171
    @nayananandvats2171 6 หลายเดือนก่อน +1

    What do we exactly mean by the term "parameter"?

    • @BAMEADManiyar
      @BAMEADManiyar 6 หลายเดือนก่อน +1

      Its value of the probability : say P(cavity). How many such values we need to maintain to have overall idea about distribution.

  • @AnshuandArika
    @AnshuandArika 3 ปีที่แล้ว +1

    How values of join prob
    Becomes 32 here ..pls help me to calculate.

    • @KnowledgeofEverything
      @KnowledgeofEverything 3 ปีที่แล้ว +3

      By Multiplying:
      Weather has 4 values and toothache, cache , cavity has 2 values each (i.e. true or false)
      Therefore
      4×2×2×2=32

    • @rajat_enzyme
      @rajat_enzyme 3 ปีที่แล้ว +1

      @@KnowledgeofEverything How the weather has 4 values?

    • @Rakeshrajeev94
      @Rakeshrajeev94 2 ปีที่แล้ว +1

      @@rajat_enzyme Its mentioned in the previous video.

    • @garbagebin3693
      @garbagebin3693 ปีที่แล้ว +1

      @@rajat_enzyme watch previous video weather is 4 (sunny, cloudy, rainy, cold)