for i in range(30, 50): x = Iris1[i, :] x = np.array([x]) g12 = np.dot(w12, x.T) + T12 g13 = np.dot(w13, x.T) + T13 g23 = np.dot(w23, x.T) + T23 if g12 > 0 and g13 > 0: newiris1.extend(x) kind1 = kind1 + 1 elif g12 < 0 and g23 > 0: newiris2.extend(x) elif g13 < 0 and g23 < 0: newiris3.extend(x)
时间: 2024-01-23 22:02:42 浏览: 33
这段代码是一个简单的三层神经网络(感知器)的分类器,用于对鸢尾花数据集进行分类。其中,Iris1是一个150x4的二维数组,表示鸢尾花数据集。每一行都代表一个鸢尾花样本,有四个特征分别是花萼长度、花萼宽度、花瓣长度和花瓣宽度。
代码中的循环遍历了Iris1数组中第30-49行的样本,对每个样本进行分类。具体来说,代码首先从Iris1数组中取出一个样本x,并将其转换为一个1x4的数组。接着,代码分别计算了三个隐藏层节点的加权输入g12、g13和g23,其中w12、w13和w23分别是从输入层到隐藏层节点的权重矩阵,T12、T13和T23是隐藏层节点的阈值。
接下来,代码根据隐藏层节点的加权输入值g12、g13和g23来对样本进行分类。如果g12和g13都为正,则将该样本分为类别1,并将其添加到newiris1数组中。如果g12为负且g23为正,则将该样本分为类别2,并将其添加到newiris2数组中。如果g13为负且g23为负,则将该样本分为类别3,并将其添加到newiris3数组中。最终,代码会返回三个类别的样本数组newiris1、newiris2和newiris3。
相关问题
for i in range(0, 30, 1): a = Iris1[i, :] - m1 a = np.array([a]) b = a.T s1 = s1 + np.dot(b, a)
这段代码是用于计算Iris1数据集的协方差矩阵s1。具体来说,代码通过循环遍历Iris1中的每个样本,并将每个样本与其对应的特征平均值m1做差,得到一个1x4的行向量a。接着,将a转置得到一个4x1的列向量b,然后通过np.dot函数计算列向量b与行向量a的点积,得到一个4x4的矩阵,将其累加到s1中。最终,s1即为Iris1数据集的协方差矩阵。
def fun3(X): O=0 for i in range(len(X)): O=O+np.square(np.sum(X[0:i+1])) return O
As an AI language model, I can infer that the given code is a Python function named "fun3" that takes a single argument X as input. The function initializes a variable "O" to zero and then iterates over the elements of the input X using a for loop. In each iteration, it calculates the square of the sum of the elements from the beginning of the input up to the current index (excluding the element at the current index) using the numpy library's "np.square" and "np.sum" functions. Finally, the function returns the value of "O", which would be the sum of the squares of the partial sums of the input X.
However, the code has some syntax errors, specifically in the line "O=O np.square(np.sum(X[0:i 1]))", where there should be an operator between "O" and "np.square". It is also unclear what the purpose of the function is or how it would be used in practice.
相关推荐
![pdf](https://img-home.csdnimg.cn/images/20210720083512.png)
![pdf](https://img-home.csdnimg.cn/images/20210720083512.png)
![pdf](https://img-home.csdnimg.cn/images/20210720083512.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)