Dhammaan ereyada

Dropout

Farsamo regularization ah oo si random ah u damiya neuron-yada intii tababarku socdo si loo yareeyo overfitting-ka.

Barashada Qoto dheer1 daqiiqo akhris

Qeexid

Intii tababarku socdo, dropout waxay si random ah eber uga dhigtaa qayb ka mid ah firaysiga (activations) tallaabo kasta, taasoo shabakadda ku qasabaysa inaysan ku tiirsanaan hal wadada. Marka la isticmaalayo (inference), dhammaan unugyadu waa firfircoon yihiin (leh cabbir-simid).

Fikrado la xiriira waxaa ka mid ah DropPath / stochastic depth gudaha qaab-dhismeedyada casriga ah.

Si fudud

Haddii xubnaha kooxdu si random ah uga maqnaadaan tababarka, qof kastaa waa inuu bartaa ciyaarta — kooxdu ma ku tiirsan karto hal xiddig oo keliya.

Halka aad ka aragto

  • MLP-yada dhaqameed iyo CNN-yada oo leh layers dropout ah.
  • Transformers badanaa waxay isticmaalaan dropout attention/residual ah.

Sida ay u shaqeyso

  1. 1.Muunad maski ah

    Si random ah eber uga dhig firaysiga isla itimaalka p.

  2. 2.Hore u gudub oo backprop

    Ku tababar shabakadda khafiifsan.

  3. 3.Dami markii inference lagu jiro

    Isticmaal shabakadda buuxda saadaalinnada.

Maxay muhiim u tahay

  • Dropout waa difaac fudud oo waxtar leh oo ka hortagaya overfitting-ka gudaha shabakadaha qoto-dheer.

Inta badan la khaldo

  • Dropout badan had iyo jeer way ka wanaagsan tahay.

    Dropout xad-dhaaf ah waxay keentaa underfitting; ku habboodhi sida hyperparameter kasta.