【免费】Neural Network Modeling using SAS Enterprise Miner-经管之家官网！

经济学管理学金融学统计学

您当前的位置> 软件培训>>

【免费】Neural Network Modeling using SAS Enterprise Miner

人大经济论坛-经管之家：分享大学、考研、论文、会计、留学、数据、经济学、金融学、管理学、统计学、博弈论、统计年鉴、行业分析包括等相关资源。
经管之家是国内活跃的在线教育咨询平台!

完整电子版已上线CDA网校，累计已有10万+在读~ 教材严格按考试大纲编写，适合CDA考生备考，也适合业务及数据分析岗位的从业者提升自我。

TOP热门关键词

专题页面精选

免费学术公开课,扫码加入

Neural Network Modeling using SAS Enterprise Miner
【语言】：英文
【页数/文件数】：600
【目录】：
Table of Contents
Chapter 1: Introduction
Chapter 2: Traditional Regression Modeling 1
2.1 The Purpose of Statistical Modeling ........................................................................... 3
2.2 Statistical Modeling Assumptions ............................................................................... 9
2.3 Checking for Outliers and Influential Data Points ..................................................... 23
2.4 Checking for Multicollinearity .................................................................................... 28
2.5 Modeling Assessment Statistics .................................................................................. 32
2.6 Bias-Variance Trade-off .............................................................................................. 39
Chapter 3: Neural Network Architecture 41
3.1 Single Layer Perceptron .............................................................................................. 43
3.2 Perceptron Training Algorithm .................................................................................... 44
3.3 Multiple Layer Perceptron Architecture ..................................................................... 47
3.4 An Explanation of the Neural Network Layers............................................................ 50
3.5 Relationship Between the Predictive Models .............................................................. 51
3.6 An Overview of the Neural Network Layers .............................................................. 53
3.7 An Overview of the Neural Network Architecture ..................................................... 63
3.8 The Objective Function ............................................................................................... 77
3.9 Neural Network Architectures .................................................................................... 84
3.10 Neural Network Hold out Method .............................................................................. 90
3.11 Optimization ................................................................................................................ 93
3.12 Numerical Examples of the Optimization Methods .................................................... 113
3.13 Numerical Examples of the Network Designs ............................................................ 126
3.14 Regularization Techniques .......................................................................................... 140
3.15 Pruning Inputs ............................................................................................................. 142
3.16 Interpretation of the Neural Network Inputs ............................................................... 145
3.17 Development to a Well-Designed Network Model ..................................................... 147
3.18 Advantages of Neural Network Modeling .................................................................. 149
3.19 The Default Settings to EM Neural Network Node .................................................... 153
Chapter 4: The NEURAL and DMREG Procedure 155
4.1 An Overview of the SAS Neural Network Procedure ................................................. 157
4.2 An Overview of the SAS DMREG Procedure ............................................................ 184
4.3 Multiple Linear Regression Example .......................................................................... 189
4.4 Autoregressive Time Series Example ......................................................................... 192
4.5 Basic Steps in Constructing the EM Diagram ............................................................. 195
Chapter 5: SAS Enterprise Miner 201
5.1 Opening the Enterprise Miner Application ................................................................. 203
5.2 Enterprise Miner Menu Options ................................................................................. 206
5.3 Option Settings to the EM Environment ..................................................................... 208
5.4 Enterprise Miner Projects and Diagrams .................................................................... 212
Chapter 6: Data Mining Using SAS Enterprise Miner 231
6.1 SEMMA ...................................................................................................................... 233
6.2 Possible Tools to the EM SEMMA Design ............................................................... 235
Chapter 7: Configuration Setup of the EM Nodes 249
7.1 Enterprise Miner Input Data Source Node .................................................................. 251
7.2 Enterprise Miner Data Partition Node ........................................................................ 279
7.3 Enterprise Miner Regression Node ............................................................................. 284
7.4 Viewing the Regression Node Results ........................................................................ 306
7.5 Model Manager ........................................................................................................... 311
7.6 Enterprise Miner Neural Network Node ..................................................................... 314
7.7 An Overview of the Advanced Neural Network Node ............................................... 331
7.8 Viewing the Neural Network Results ......................................................................... 362
7.9 Neural Network Interactive Training .......................................................................... 372
7.10 Enterprise Miner Assessment Node ............................................................................ 383
7.11 Enterprise Miner SAS Code Node .............................................................................. 409
7.12 Enterprise Miner Reporter Node ................................................................................. 426
Chapter 8: Comparing Prediction Estimates 457
8.1 Comparing Multiple Linear Regression Estimates ..................................................... 462
8.2 Comparing Nonlinear Regression Estimates .............................................................. 466
8.3 Comparing Logistic Regression Estimates ................................................................. 475
8.4 Comparing Autoregressive Time Series Estimates ..................................................... 504
8.5 Comparing Discriminant Analysis Estimates ............................................................. 533
Appendix 557
References 577
Book Index 581
http://www.sasenterpriseminer.com/images/SAS%20Neural%20Network%20Modeling%20Using%20SAS%20Enteprise%20Miner%20Front%20Cover.jpg
其实这个书在数据挖掘版块有，但是那个楼主收的钱太多了，现在照顾一下穷人，特意免费贡献。

「经管之家」APP：经管人学习、答疑、交友，就上经管之家！
免流量费下载资料----在经管之家app可以下载论坛上的所有资源，并且不额外收取下载高峰期的论坛币。
涵盖所有经管领域的优秀内容----覆盖经济、管理、金融投资、计量统计、数据分析、国贸、财会等专业的学习宝库，各类资料应有尽有。
来自五湖四海的经管达人----已经有上千万的经管人来到这里，你可以找到任何学科方向、有共同话题的朋友。
经管之家（原人大经济论坛），跨越高校的围墙，带你走进经管知识的新世界。
扫描下方二维码下载并注册APP

本文关键词：

本文论坛网址：https://bbs.pinggu.org/thread-482740-1-1.html

上一篇 | 土地经济学知名教授钱忠好论文全集

下一篇 | 安达信雅格尔营销库存管理

SAS软件培训精彩帖子推荐更多

您可能感兴趣的文章

本站推荐的文章

人气文章

本文标题：【免费】Neural Network Modeling using SAS Enterprise Miner

本文链接网址：https://bbs.pinggu.org/jg/ruanjianpeixun_sasruanjianpeixun_482740_1.html

1.凡人大经济论坛-经管之家转载的文章,均出自其它媒体或其他官网介绍,目的在于传递更多的信息,并不代表本站赞同其观点和其真实性负责；
2.转载的文章仅代表原创作者观点,与本站无关。其原创性以及文中陈述文字和内容未经本站证实,本站对该文以及其中全部或者部分内容、文字的真实性、完整性、及时性，不作出任何保证或承若；
3.如本站转载稿涉及版权等问题,请作者及时联系本站,我们会及时处理。

【免费】Neural Network Modeling using SAS Enterprise Miner-经管之家官网！

SAS软件培训