乳腺癌python脚本 此脚本包括参数设置,自动调优,数据规范化,概率计算,分类预测等等 # -*- coding: utf-8 -*- """ @author: QQ:231469242 """ #标准化数据 from sklearn import preprocessing from sklearn.svm import SVC from sklearn.datasets import load_breast_cancer from sklearn.model_selection impor...
decision_function()的功能:计算样本点到分割超平面的函数距离,分割超平面一边数据是正数,一边是负数,如果是二分类,正数代表一类,负数代表另一类 乳腺癌python脚本 此脚本包括参数设置,自动调优,数据规范化,概率计算,分类预测等等 #-*-coding:utf-8-*-""" @author:QQ:231469242金融现金贷用户数据分析和用户画像 https...
python实现 样本集下载:https:///626626cdllp/data-mining/blob/master/SVM/testSet.txt # -*- coding:UTF-8 -*- import matplotlib.pyplot as plt import numpy as np import random # 简化版smo # 函数说明:读取数据 def loadDataSet(fileName): alldata = np.loadtxt(fileName) dataMat = alldata[:...
# -*- coding: utf-8 -*- """main.py""" import geatpy as ea # import geatpy from MyProblem import MyProblem # 导入自定义问题接口 if __name__ == '__main__': # 实例化问题对象 problem = MyProblem() # 构建算法 algorithm = ea.soea_DE_rand_1_bin_templet(problem, ea.Population(...
# -*- coding: utf-8 -*- __author__ = 'Wsine' from numpy import * import matplotlib.pyplot as plt import operator import time def loadDataSet(fileName): dataMat = [] labelMat = [] with open(fileName) as fr: for line in fr.readlines(): lineArr = line.strip().split('\t') ...
#-*-coding:GBK -*- from sklearn import svm import numpy as np from sklearn import model_selection from sklearn.model_selection import GridSearchCV from sklearn.model_selection import train_test_split def init(s): it = {b'Iris-setosa': 0, b'Iris-versicolor': 1, b'Iris-virginica': ...
# -*- coding:utf-8 -*- #svm.py importnumpy as np importmatplotlib.pyplot as plt importrandom defgetdata(num):# 生成间隔大些的数据,需要输入数据量 xdata=[] foriinrange(num): idata=[random.randint(0,20), random.randint(0,20)] ...
# -*- coding: utf-8 -*- import os import numpy as nppath = "wine/wine.txt"data = np.loadtxt(path,dtype=float,delimiter=",")print(data)yy, x = np.split(data, (1,), axis=1)print(yy.shape, x.shape)y = []for n in yy: y.append(int(n))train_data = np.concatenate((x...
# -*- coding:utf-8 -*- # /usr/bin/python import time import pandas as pd import numpy as np from sklearn.model_selection import train_test_split import matplotlib.pyplot as plt from tqdm import tqdm class SVM(): def __init__(self,maxIter,kernel="linear"): '''参数''' self.maxIte...
/usr/bin/python#-*-coding:utf-8-*-importnumpyasnp from sklearnimportsvm from scipyimportstats from sklearn.metricsimportaccuracy_scoreimportmatplotlibasmplimportmatplotlib.pyplotasplt defextend(a,b,r):x=a-b m=(a+b)/2returnm-r*x/2,m+r*x/2if__name__=="__main__":np.random.seed(...