Linear regression model with individual intercepts. This class gives first order information (gradient and loss) for this model
fit_intercept : bool, default=`True`
If
True, the model uses an intercept
features : numpy.ndarray, shape=(n_samples, n_features) (read-only)
The features matrix
labels : numpy.ndarray, shape=(n_samples,) (read-only)
The labels vector
n_samples : int (read-only)
Number of samples
n_features : int (read-only)
Number of features
n_coeffs : int (read-only)
Total number of coefficients of the model
n_threads : int, default=1 (read-only)
Number of threads used for parallel computation.
if
int <= 0: the number of threads available on the CPUotherwise the desired number of threads