Internals
Others
EvoLinear.Linear.update_∇!
— Functionupdate_∇!(L, ∇¹, ∇², x, y, p, w)
Update gradients w.r.t each feature. Each feature gradient update is dispatch according to the loss type (mse
, logistic
...).
EvoLinear.Linear.predict_linear
— Functionpredict_linear(m, x)
Returns the predictions on the linear basis from model m
using the features matrix x
.
Arguments
m::EvoLinearModel
: model generating the predictions.x
: features matrix[nobs, num_features]
for which predictions are generated.
EvoLinear.Linear.predict_proj
— Functionpredict_proj(m, x)
Returns the predictions on the projected basis from model m
using the features matrix x
.
MSE
:pred_proj = pred_linear
Logistic
:pred_proj = sigmoid(pred_linear)
Poisson
:pred_proj = exp(pred_linear)
Gamma
:pred_proj = exp(pred_linear)
Tweedie
:pred_proj = exp(pred_linear)
Arguments
m::EvoLinearModel
: model generating the predictions.x
: features matrix[nobs, num_features]
for which predictions are generated.