jijzepttools.blackbox_optimization.factorization_machine

Classes

FactorizationMachine	Factorization Machine model
FMTrainer

Module Contents

class FactorizationMachine(n_features: int, latent_dim: int)

Bases: torch.nn.Module

Factorization Machine model

`math f(x|w, v) = w0 + Σwi*xi + ΣΣ<vj, vk>xj*xk = w0 + Σwi*xi + 1/2*(Σ(vi*xi)^2 - Σ(vi^2*xi^2)) `

n_features

latent_dim

linear

quad

forward(x)

property v

property w

property w0

class FMTrainer(n_features: int, latent_dim: int, optimizer_params: dict | None = None)

model

fit(x_numpy: numpy.ndarray, y_numpy: numpy.ndarray, n_epochs: int)

predict(x: torch.Tensor) → torch.Tensor

property x

property y

get_qubo() → tuple[numpy.ndarray, float]