names.insert(0,'yinwenqiao')#指定位置添加元素 # print('before ',names) # print('pop返回值:',names.pop()) # print('remove 方法的返回值',names.remove('yinwenqiao')) # del names[0]#使用del关键字删除指定元素 # names.pop()#默认删除最后一个元素,删谁也把它的值返回了 # names.pop(2)...
一、random模块的使用: Python中的random模块用于生成随机数。下面介绍一下random模块中最常用的几个函数。 1、常用函数: (1)random.random() 用于生成一个0到1的随机符点数: 0 <= n < 1.0 (2)random.uniform(a,b) 用于生成一个指定范围内的随机符点数,两个参数其中一个是上限,一个是下限。如果a > b,...
44print(random.choice(names))4546#从给定的列表中随机取3个元素。47print(random.sample(names,3))4849#取值(1,3)的float类型。50print(random.uniform(1,3)) 以上代码执行结果 二.验证码案例 1#!/usr/bin/env python2#_*_coding:utf-8_*_3#@author :yinzhengjie4#blog:http://www.cnblogs.com/yin...
HaikunatorPY Generate Heroku-like random names to use in your python applications. Installation pip install haikunator Usage Haikunator is pretty simple. There is nothing to configure and it only has a single method,haikunate: fromhaikunatorimportHaikunatorhaikunator=Haikunator()# haikunator = Haik...
Logged in users can view full social security numbers and can save their fake names to use later. Cynthia K. Carrera 1699 Travis Street Doral, FL 33166 Curious whatCynthiameans?Click here to find out! Mother's maiden name Borchert SSN ...
import sys.builtin_module_names #返回内建模块的名字modules 查看所有可用模块的名字1.1.1获取当前日期和时间 + View Code 1.1.2 datetime与str str转换成datetime:strptime() datetime转换成str:strftime() 先格式化一个格式:('%Y-%m-%d %H:%M:%S') + View Code 1.1.3 calendar 1 2 import calendar ...
#write.table(importance_otu,'importance_otu.txt',sep='\t',col.names=NA,quote=FALSE) 此处“Mean Decrease Accuracy”和“Mean Decrease Gini”为随机森林模型中的两个重要指标。其中,“mean decrease accuracy”表示随机森林预测准确性的降低程度,该值越大表示该变量的重要性越大;“mean decrease gini”计算每...
(cancer.data, columns=cancer.feature_names)y = cancer.target# 数据预处理scaler = StandardScaler()X_scaled = scaler.fit_transform(X)X_train, X_test, y_train, y_test = train_test_split(X_scaled, y, test_size=0.2, random_state=42)# 构建随机森林模型rf_model = RandomForestClassifier(n_...
feature_names=[f'feature {i}'foriinrange(X.shape[1])]feature_namesOut[25]:['feature 0','feature 1','feature 2','feature 3','feature 4','feature 5','feature 6','feature 7','feature 8','feature 9']importances=rf.feature_importances_## 模型会自动输出变量重要程度指标std=np.std...
otu <- otu[rownames(plant), ] otu <- cbind(otu, plant) #为了方便后续评估随机森林模型的性能 #将总数据集分为训练集(占 70%)和测试集(占 30%) set.seed(123) train <- sample(nrow(otu), nrow(otu)*0.7) otu_train <- otu[train, ] ...