moge19的专栏

1、导入编程库。 import matplotlib.pyplot as plt import numpy as np import tensorflow as tf from sklearn import datasets 2、创建会话，加载数据 sess = tf.Session() iris = datasets.load_iris() x_vals = np.array([...

1、导入必要的编程库，创建计算图，加载数据集 import matplotlib.pyplot as plt import numpy as np import tensorflow as tf from sklearn import datasets sess = tf.Session() iris = datasets.load_iris() x_vals = np.array([x...

1、导入必要编程库 import matplotlib.pyplot as plt import numpy as np import tensorflow as tf from sklearn import datasets 2、创建会话，生成模拟数据 sess = tf.Session() (x_vals, y_vals) = datasets.make_circles(n_s...

1、戴明回归算法 戴明回归最小化，求的是点到回归直线的距离。具体是最小化x值和y值两个方向的误差。 2、Tensorflow实现戴明回归算法 （1）导入编程库，创建会话等 import matplotlib.pyplot as plt import numpy as np import tensorflow as tf from sklearn import datasets s...

1、导入必要的编程库； import matplotlib.pyplot as plt import numpy as np import tensorflow as tf from sklearn import datasets sess = tf.Session() 2、加载iris数据集并为每类分离目标值； iris = datasets.load_iris() x_vals = np....

1、创建计算会话，导入必要的编程库。 import matplotlib.pyplot as plt import numpy as np import tensorflow as tf from sklearn import datasets sess = tf.Session() 2、加载Iris数据集 iris = datasets.load_iris() x_vals = np.arr...

import matplotlib.pyplot as plt import numpy as np import tensorflow as tf from sklearn import datasets sess = tf.Session() iris = datasets.load_iris() x_vals= np.array([[x[0], x[3]] for x in iris.da...

1、导入编程库 import random import numpy as np import tensorflow as tf import matplotlib.pyplot as plt from PIL import Image from tensorflow.examples.tutorials.mnist import input_data 2、创建会话，加载数据集 sess =...