Reducts and Core | Rough Set Theory | Dispensable and Indispensable Attributes

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  • เผยแพร่เมื่อ 3 ธ.ค. 2024

ความคิดเห็น • 18

  • @dzordrezord9820
    @dzordrezord9820 5 ปีที่แล้ว +3

    Thanks, waiting for more course on rough sets

  • @perumallalalithasaisatyava7803
    @perumallalalithasaisatyava7803 4 ปีที่แล้ว

    Nice explaination
    plz explain similarity based attribute reduction in rough set theory in clustering perspective

  • @souravbhagat1358
    @souravbhagat1358 2 ปีที่แล้ว

    Pls make a vedio on Gradient Descend Algorithm or Generalized Delta Learning Rule .
    I need this vedio my exam is very soon ..

  • @ananyagupta2350
    @ananyagupta2350 4 ปีที่แล้ว

    Please please upload more videos on fuzzy logic subject

  • @vinaymuley3692
    @vinaymuley3692 5 ปีที่แล้ว

    Introduction:1.1 Biological neurons, McCulloch and Pitts models of neuron, Types
    of activation function, Network architectures, Knowledge representation, Hebb net
    1.2 Learning processes: Supervised learning, Unsupervised learning and
    Reinforcement learning
    1.3 Learning Rules : Hebbian Learning Rule, Perceptron Learning Rule, Delta
    Learning Rule, Widrow-Hoff Learning Rule, Correlation Learning Rule, WinnerTake-All Learning Rule
    1.4 Applications and scope of Neural Networks
    10
    2
    Supervised Learning Networks :
    2.1 Perception Networks - continuous & discrete, Perceptron convergence theorem,
    Adaline, Madaline, Method of steepest descent, - least mean square algorithm,
    Linear & non-linear separable classes & Pattern classes,
    2.2 Back Propagation Network,
    2.3 Radial Basis Function Network.
    12
    3
    Unsupervised learning network:
    3.1 Fixed weights competitive nets,
    3.2 Kohonen Self-organizing Feature Maps, Learning Vector Quantization,
    3.3 Adaptive Resonance Theory - 1
    06
    4
    Associative memory networks:
    4.1 Introduction, Training algorithms for Pattern Association,
    4.2 Auto-associative Memory Network, Hetero-associative Memory Network,
    Bidirectional Associative Memory,
    4.3 Discrete Hopfield Networks.
    08
    5
    Fuzzy Logic:
    5.1 Fuzzy Sets, Fuzzy Relations and Tolerance and Equivalence
    5.2 Fuzzification and Defuzzification
    5.3 Fuzzy Controllers

    • @bbjjooddhh
      @bbjjooddhh 4 ปีที่แล้ว

      Do you have a pdf of this?

  • @shekhar9119
    @shekhar9119 ปีที่แล้ว

    Pls provide the pdf of your notes it will be highly beneficial for me

  • @ranideybca-078
    @ranideybca-078 ปีที่แล้ว

    Why not for q and r

  • @ruthless4563
    @ruthless4563 5 ปีที่แล้ว

    Bro Max net, Mexican hat and hamming net ka bhi daldo plz...

  • @arulanandamkajavatan7090
    @arulanandamkajavatan7090 5 ปีที่แล้ว

    how to find rules sir

    • @btechtutorialByNishantMittal
      @btechtutorialByNishantMittal  5 ปีที่แล้ว +1

      Which rules?

    • @arulanandamkajavatan7090
      @arulanandamkajavatan7090 5 ปีที่แล้ว

      @@btechtutorialByNishantMittal from a given data set how to mine knowledge (RULES ) using roughset

    • @souravbhagat1358
      @souravbhagat1358 2 ปีที่แล้ว

      Pls Make a vedio on Generalised Delta learning rule and Gradient Descend algorithm because apke jaisa vedio puti youtube pr khi nhi hai

  • @Ani3479
    @Ani3479 5 ปีที่แล้ว +1

    Video banate reh bhai!

  • @malihajalil9219
    @malihajalil9219 4 ปีที่แล้ว +1

    Wo bi smj nhi aie ya bi nhi😔

  • @KaushalSoni2205
    @KaushalSoni2205 2 ปีที่แล้ว

    R ki jagah koi other symbol use kro

  • @ranideybca-078
    @ranideybca-078 ปีที่แล้ว

    Please ans it

  • @Anilkumar-Ch17
    @Anilkumar-Ch17 ปีที่แล้ว +2

    Please don't repeat tt tt at end of every word