tensorflow基础篇-2

#-*- coding:utf-8 -*-
import tensorflow as tf
sess=tf.Session()

#整流水线单元relu
print sess.run(tf.nn.relu([-3.,3,10.]))

#抵消relu激励函数的线性增长部分
print sess.run(tf.nn.relu6([-3.,3.,10.]))

#segmoid函数：1/(1+exp(-x))
print sess.run(tf.nn.sigmoid([-1.,0.,1.]))

#双面正切segmoid：(exp(x)-exp(-x))/(exp(x)+exp(-x))
print sess.run(tf.nn.tanh([-1.,0.,1.]))

#softsign:x/(abs(x)+1)
print sess.run(tf.nn.softsign([-1.,0.,1.]))

#softplus:log(exp(x)+1)
print sess.run(tf.nn.softplus([-1.,0.,1.]))

#ELU激励函数：(exp(-x)+1) if x<0 else x
print sess.run(tf.nn.elu([-1.,0.,1.]))

#-*- coding:utf-8 -*-
from sklearn import datasets
#加载鸢尾花卉数据集:
#                  150数据集
#                  每个数据集50个样本
iris=datasets.load_iris()
print len(iris.data)
print len(iris.target)
print iris.target[0]
print set(iris.target)

# #加载波士顿房价，506个放假样本，14个特征值
import requests
housing_url='https://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data'
housing_header=['CRIM','ZN','INDUS','CHAS','NOX','RM','AGE','DIS','RAD','TAX','PTRATIO','B','LSTAT','MEDV0']
housing_file=requests.get(housing_url)
print housing_file.text
housing_data=[[float(x) for x in y.split(' ') if len(x)>=1] for y in housing_file.text.split('
') if len(y)>=1]
print len(housing_data)
print len(housing_data[0])

#MNIST手写字体库
from tensorflow.examples.tutorials.mnist import input_data
mnist=input_data.read_data_sets("MNIST_data",one_hot=True)
print len(mnist.train.images)
print mnist.train.images
print len(mnist.test.images)
print mnist.test.images
print len(mnist.validation.images)
print mnist.validation.images
print mnist.train.labels[1,:]