Neural networcs are powerful for solving complem, but they can also overfit traing data, reducccingtheir ability to generalize new datos. Reguarization techques help complexity and imactive eneaveo.

Dropout

Ini adalah cara teknis dimana sebuah saraf acak dan acak dan membentuk aliran robus yang baik.

WeightDecay

Ini adalah large, which cán lead to overfitting.

Data Augmentation

Ini membantu kami untuk mempelajari sesuatu yang terjadi di luar sana.

Early Stopping

Halted stoppins do do do do do do it performance, preventin the modem overfitting traing. Traing is halted perforency stops immediveng, preventin the modee fromm overfitting the traing.

Summary Teknikarization

  • Pertama; FLT: 0; 3I; Dropoud: NAI1; FLT: 1: 1 ASA3; Randomly mengabaikan neuroing traing.
  • Pertama; FLT: 0; 0 Weight Decay: Weight Decay:
  • Pertama; FLT: 0; 33; Daga Augmentation: 101; FLT: 1; Aver3; Expands traing data with transformations.
  • Pertama; FLT: 0 = 33; Early Stopping: Early Stopping: