import numpy as np import matplotlib.pyplot as plt from sklearn.svm import SVC class MySVM: X=[];y=[] m=0;n=0 fignum=1 def __init__(self,params={ 'kernel': 'linear'}): self.moduleparams=params self.module=SVC(**params) @classmethod def load_data(cls,input_file): X = [];y = [] with open(input_file, 'r') as f: for line in f.readlines(): data = [float(x) for x in line.split(',')] X.append(data[:-1]) y.append(data[-1]) cls.X = np.array(X) cls.y= np.array(y) @classmethod def plot_data(cls): class_0 = np.array([cls.X[i] for i in range(len(cls.X)) if
SVC实现分类算法实现
最新推荐文章于 2025-05-31 11:00:00 发布