KELMOR and IKELMOR

import os
from copy import deepcopy
import pandas as pd
from pathlib import Path
import numpy as np
from sklearn.metrics import accuracy_score
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split
from numpy.linalg import inv
from sklearn.utils.validation import check_X_y
from sklearn import preprocessing
from sklearn.base import ClassifierMixin, BaseEstimator
from sklearn.metrics.pairwise import pairwise_kernels, pairwise_distances
 
 
class KELMOR(ClassifierMixin, BaseEstimator):
    def __init__(self,C=10, method="full", S=None, eps=1e-5, kernel="linear", gamma=0.1, degree=3, coef0=1, kernel_params=None):
        self.C = C
        self.kernel = kernel
        self.method = method
        self.S = S
        self.eps = eps
        self.gamma = gamma
        self.degree = degree
        self.coef0 = coef0
        self.kernel_params = kernel_params
 
    def fit(self, X, y):
        X, y = check_X_y(X,y)
        self.X, self.y = X, y
        n, d = X.shape
        # ---------------规范化类别标签：0,1,2,3,4,5-----------------
        self.le_ = preprocessing.LabelEncoder()
        self.le_.fit(y)
        y = self.le_.transform(y)
        #  --------------------------------------------------------
        classes = np.unique(y)
        nclasses = len(classes)