Table 27 Description of the parameters used in the best classifier

Penalty to minimize cost function (penalty)

l2

Additive smoothing (alpha)

Laplace

Dual formulation (dual)

Primal formulation

Learn class prior probabilities (fit_prior)

True

Tolerance level for stopping criteria (tol)

1.00E-04

Relative strength of regularization (c)

1

Calculate the intercept (fit_intercept)

True

Intercept scaling (intercept_scaling)

1

Pseudo-random number generator (random_state)

0

Solver algorithm (solver)

L-BFGS

Number of maximum iteration(max_iter)

100

Approach for handling multiple classes (multi_class)

multinomial