lstm算法数据集的相关内容

文章 2022-07-26 来自：开发者社区

DL之LSTM：基于tensorflow框架利用LSTM算法对气温数据集训练并回归预测

目录输出结果核心代码输出结果数据集 tensorboard可视化 1. iter: 0 loss: 0.010328549 2. iter: 500 loss: 0.0044991444 3. iter: 1000 loss: 0.003714567 4. iter: 1500 loss: 0.0033356838 5. iter: 200....

文章 2022-07-26 来自：开发者社区

TF之LSTM：基于tensorflow框架自定义LSTM算法实现股票历史(1990~2015数据集,6112预测后100+单变量最高)行情回归预测

目录输出结果LSTM代码输出结果数据集 LSTM代码1. def LSTM(batch): 2. w_in=weights['in'] 3. b_in=biases['in'] 4. input_rnn=tf.matmul(input,w_in)+b_in 5. inp...

文章 2022-07-25 来自：开发者社区

TF之LSTM：利用基于顺序的LSTM回归算法对DIY数据集sin曲线(蓝虚)预测cos(红实)(matplotlib动态演示)—daiding

目录输出结果代码设计输出结果代码设计1. import tensorflow as tf 2. import numpy as np 3. import matplotlib.pyplot as plt 4. 5. BATCH_START = 0 6. TIME_STEPS = 20 7. BATCH_SIZE = 50 .....

文章 2022-07-23 来自：开发者社区

TF之LSTM：利用多层LSTM算法对MNIST手写数字识别数据集进行多分类

目录设计思路实现代码设计思路更新……实现代码# -*- coding:utf-8 -*- import tensorflow as tf import numpy as np from tensorflow.contrib import rnn from tensorflow.examples.tutorials.mnist import input_data #根据电脑情况设置 GPU con....

文章 2022-02-17 来自：开发者社区

TF之LSTM：利用基于顺序的LSTM回归算法对DIY数据集sin曲线(蓝虚)预测cos(红实)(matplotlib动态演示)—daiding

输出结果代码设计import tensorflow as tfimport numpy as npimport matplotlib.pyplot as pltBATCH_START = 0 TIME_STEPS = 20 BATCH_SIZE = 50 INPUT_SIZE = 1 OUT....

文章 2022-02-17 来自：开发者社区

TF之LSTM：利用多层LSTM算法对MNIST手写数字识别数据集进行多分类

设计思路网络异常，图片无法展示|实现代码 # -*- coding:utf-8 -*-import tensorflow as tfimport numpy as npfrom tensorflow.contrib import rnnfrom tensorflow.examples.tutorials.mnist import input_data#根据电脑情况设置 GPUconfi....

文章 2022-02-17 来自：开发者社区

DL之LSTM：基于tensorflow框架利用LSTM算法对气温数据集训练并回归预测

输出结果tensorboard可视化iter: 0 loss: 0.010328549iter: 500 loss: 0.0044991444iter: 1000 loss: 0.003714567iter: 1500 loss: 0.0033356838iter: 2000 loss: 0.003116763iter: 2500 loss: 0.0029606873iter: 3000 los....

文章 2022-02-17 来自：开发者社区

TF之LSTM：基于tensorflow框架自定义LSTM算法实现股票历史(1990~2015数据集,6112预测后100+单变量最高)行情回归预测

输出结果数据集LSTM代码def LSTM(batch):          w_in=weights['in']    b_in=biases['in']    input_rnn=tf.matmul(input,w_in)+b_in    input_rnn=tf.reshape(.....

文章 2022-02-17 来自：开发者社区

TF之LSTM：利用LSTM算法对Boston(波士顿房价)数据集【13+1,506】进行回归预测(房价预测)（二）

核心代码    def add_input_layer(self,):        l_in_x = tf.reshape(self.xs, [-1, self.input_size], name='2_2D')          Ws_in = self._weight_variab....

文章 2022-02-17 来自：开发者社区

TF之LSTM：利用LSTM算法对Boston(波士顿房价)数据集【13+1,506】进行回归预测(房价预测)(一)

输出结果boston.data： (506, 13)[[6.3200e-03 1.8000e+01 2.3100e+00 0.0000e+00 5.3800e-01 6.5750e+00 6.5200e+01 4.0900e+00 1.0000e+00 2.9600e+02 1.5300e+01 3.9690e+02 4.9800e+00] [2.7310e-02 0.0....

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