ml_ANN_MLP_TrainFlags
import { ml_ANN_MLP_TrainFlags } from '@banou/opencv-wasm'Use after await initOpenCV(). See the initialization and named imports guide.
Native object: release it with using or delete(). Factories can return null; check before calling methods.
ml_ANN_MLP_TrainFlags: Train options
Constructors and members
static UPDATE_WEIGHTS
Update the network weights, rather than compute them from scratch. In the latter case the weights are initialized using the Nguyen-Widrow algorithm.
UPDATE_WEIGHTS: ml_ANN_MLP_TrainFlagsValue<1>,static NO_INPUT_SCALE
Do not normalize the input vectors. If this flag is not set, the training algorithm normalizes each input feature independently, shifting its mean value to 0 and making the standard deviation equal to 1. If the network is assumed to be updated frequently, the new training data could be much different from original one. In this case, you should take care of proper normalization.
NO_INPUT_SCALE: ml_ANN_MLP_TrainFlagsValue<2>,static NO_OUTPUT_SCALE
Do not normalize the output vectors. If the flag is not set, the training algorithm normalizes each output feature independently, by transforming it to the certain range depending on the used activation function.
NO_OUTPUT_SCALE: ml_ANN_MLP_TrainFlagsValue<4>These signatures describe this package. Upstream documentation can mention optional backends that are absent from this build. Check runtime compatibility before choosing a backend or file format.