Python实现鸢尾花数据集分类问题——基于skearn的SVM 代码如下: # !/usr/bin/env python # encoding: utf-8 __author__ = 'Xiaolin Shen' from sklearn import svm import numpy as np from sklearn import model_selection import matplotlib.pyplot as plt import matplotlib as mpl from m
iris二分类 # Linear Support Vector Machine: Soft Margin # ---------------------------------- # # This function shows how to use TensorFlow to # create a soft margin SVM # # We will use the iris data, specifically: # x1 = Sepal Length # x2 = Petal Width
1.1 流程控制之for循环 1 迭代式循环:for,语法如下 for i in range(10): 缩进的代码块 2 break与continue(同上) 3 循环嵌套 for i in range(1,10): for j in range(1,i+1): print('%s*%s=%s' %(i,j,i*j),end=' ') print() for+else 1.2 开发工具IDE 1.2.1 为何要用IDE 到现在为止,我们也是写过代码的人啦,但你有没有发现,每次写代码要新建文件.写
今天给大家写广义混合效应模型Generalised Linear Random Intercept Model的第一部分 ,混合效应logistics回归模型,这个和线性混合效应模型一样也有好几个叫法: Mixed Effects Logistic Regression is sometimes also called Repeated Measures Logistic Regression, Multilevel Logistic Regression and Multilevel Bina