castingA3T的博客

单链表python中没有实现 单链表由两部分组成：数据+下一个节点的地址 python实现：节点类+单链表操作类。item存放数据，next存放下一个节点的实例化对象 class Node(object): """创建节点类""" def __init__(self, item): # item存放数据 self.item = item # 指向后继节点，新节点默认为None # 下一个节点对象 self

# -*- coding: utf-8 -*- """ Created on Thu Feb 1 13:33:50 2018 @author: Administrator """ import pandas as pd path='F:/python/3python数据分析与挖掘实战/图书配套数据、代码/chapter5/demo/data/bankloan.xls' df=pd.read_

import pandas as pd #df=pd.read_csv('data_singlevar.txt',sep=',',header=None) f=open('F:/python/4python机器学习经典案例/Python-Machine-Learning-Cookbook-master/Chapter01/data_singlevar.txt') df=pd.read_csv(f

# -*- coding: utf-8 -*- """ Created on Tue Jan 30 19:17:44 2018 @author: Administrator """ import numpy as np from sklearn.tree import DecisionTreeRegressor from sklearn.ensemble import AdaBoostRegr

# -*- coding: utf-8 -*- """ Created on Mon Jan 29 22:57:10 2018 @author: Administrator """ import matplotlib.pyplot as plt import numpy as np from sklearn.linear_model import LinearRegression#导入线性回归

import numpy as np import matplotlib.pyplot as plt#给定x,y两组数据 x=np.array([1,7,4,6,2,9,3,5,7,3,5,9,7,8,2,4,3,1,2,4,4,2]) y=np.array([8,3,10,5,12,2,9,11,1,20,4,7,8,4,3,2,5,1,6,5,15,15]) #plt.scatter(x,y)#

from sklearn.svm import SVC import numpy as np X= np.array([[-1,-1],[-2,-1],[1,1],[2,1]]) #特征样本 y = np.array([1,1,2,2]) #分类标记 clf = SVC(kernel='linear') #线性核函数 clf.fit(X,y) #训练模型，自动分类 prin

#首先随机创建一些二维数据作为训练集，选择二维特征数据，主要是方便可视化 from numpy import concatenate,column_stack,row_stack import numpy as np import matplotlib.pyplot as plt #%matplotlib inline from sklearn.datasets.samples_generator

#多项式拟合(从给定的x,y中解析出最接近数据的方程式) #要拟合的x,y数据 x = np.arange(1, 17, 1) y = np.array([4.00, 6.40, 8.00, 8.80, 9.22, 9.50, 9.70, 9.86, 10.00, 10.20, 10.32, 10.42, 10.50, 10.55, 10.58, 10.60]) z1 = np.polyfit(x,