Normalization
In creating a database, normalization is the process of organizing it into tables in such a way that the results of using the database are always unambiguous and as intended. Normalization may have the effect of duplicating data within the database and often results in the creation of additional tables. (While normalization tends to increase the duplication of data, it does not introduce redundancy, which is unnecessary duplication.) Normalization is typically a refinement process after the initial exercise of identifying the data objects that should be in the database, identifying their relationships, and defining the tables required and the columns within each table.
A simple example of normalizing data might consist of a table showing:
Customer | Item purchased | Purchase price |
Thomas | Shirt | $40 |
Maria | Tennis shoes | $35 |
Evelyn | Shirt | $40 |
Pajaro | Trousers | $25 |
If this table is used for the purpose of keeping track of the price of items and you want to delete one of the customers, you will also delete a price. Normalizing the data would mean understanding this and solving the problem by dividing this table into two tables, one with information about each customer and a product they bought and the second about each product and its price. Making additions or deletions to either table would not affect the other.
Normalization degrees of relational database tables have been defined and include:
First normal form (1NF). This is the "basic" level of normalization and generally corresponds to the definition of any database, namely:
- It contains two-dimensional tables with rows and columns.
- Each column corresponds to a sub-object or an attribute of the object represented by the entire table.
- Each row represents a unique instance of that sub-object or attribute and must be different in some way from any other row (that is, no duplicate rows are possible).
- All entries in any column must be of the same kind. For example, in the column labeled "Customer," only customer names or numbers are permitted.
Second normal form (2NF). At this level of normalization, each column in a table that is not a determiner of the contents of another column must itself be a function of the other columns in the table. For example, in a table with three columns containing customer ID, product sold, and price of the product when sold, the price would be a function of the customer ID (entitled to a discount) and the specific product.
Third normal form (3NF). At the second normal form, modifications are still possible because a change to one row in a table may affect data that refers to this information from another table. For example, using the customer table just cited, removing a row describing a customer purchase (because of a return perhaps) will also remove the fact that the product has a certain price. In the third normal form, these tables would be divided into two tables so that product pricing would be tracked separately.
Domain/key normal form (DKNF). A key uniquely identifies each row in a table. A domain is the set of permissible values for an attribute. By enforcing key and domain restrictions, the database is assured of being freed from modification anomalies. DKNF is the normalization level that most designers aim to achieve.
Normalization的更多相关文章
- 数据预处理中归一化(Normalization)与损失函数中正则化(Regularization)解惑
背景:数据挖掘/机器学习中的术语较多,而且我的知识有限.之前一直疑惑正则这个概念.所以写了篇博文梳理下 摘要: 1.正则化(Regularization) 1.1 正则化的目的 1.2 正则化的L1范 ...
- 归一化方法 Normalization Method
1. 概要 数据预处理在众多深度学习算法中都起着重要作用,实际情况中,将数据做归一化和白化处理后,很多算法能够发挥最佳效果.然而除非对这些算法有丰富的使用经验,否则预处理的精确参数并非显而易见. 2. ...
- 归一化交叉相关Normalization cross correlation (NCC)
归一化交叉相关Normalization cross correlation (NCC) 相关系数,图像匹配 NCC正如其名字,是用来描述两个目标的相关程度的,也就是说可以用来刻画目标间的相似性.一般 ...
- 从Bayesian角度浅析Batch Normalization
前置阅读:http://blog.csdn.net/happynear/article/details/44238541——Batch Norm阅读笔记与实现 前置阅读:http://www.zhih ...
- quantile normalization原理
对于芯片或者其它表达数据来说,最常见的莫过于quantile normalization啦. 那么它到底对我们的表达数据做了什么呢?首先要么要清楚一个概念,表达矩阵的每一列都是一个样本,每一行都是一个 ...
- 数据标准化 Normalization
数据的标准化(normalization)是将数据按比例缩放,使之落入一个小的特定区间.在某些比较和评价的指标处理中经常会用到,去除数据的单位限制,将其转化为无量纲的纯数值,便于不同单位或量级的指标能 ...
- [CS231n-CNN] Training Neural Networks Part 1 : activation functions, weight initialization, gradient flow, batch normalization | babysitting the learning process, hyperparameter optimization
课程主页:http://cs231n.stanford.edu/ Introduction to neural networks -Training Neural Network ________ ...
- 深度学习网络层之 Batch Normalization
Batch Normalization Ioffe 和 Szegedy 在2015年<Batch Normalization: Accelerating Deep Network Trainin ...
- Batch Normalization
一.BN 的作用 1.具有快速训练收敛的特性:采用初始很大的学习率,然后学习率的衰减速度也很大 2.具有提高网络泛化能力的特性:不用去理会过拟合中drop out.L2正则项参数的选择问题 3.不需要 ...
随机推荐
- [Android]学习笔记之布局
5大布局,其中前3个是常用的,第四个绝对布局已经提示deprecated 判断表达式 if test (表达式为真) if test !表达式为假 test 表达式1 –a 表达式2 两个表达式都为真 test 表达式1 –o 表达式 ...
- HttpCache缓存扩展方法
using System;using System.Collections;using System.Configuration;using System.Web;using System.Web.C ...
- JS树形菜单
超全的JS树形菜单源代码共享(有实例图) 树形菜单是很常用的效果,常用在管理软件当中,但是一套树形菜单已经不能满足需求,所以如果能有一套比较全面的树形菜单JS特效代码,将会非常方便,下面懒人萱将超全的 ...
- OpencV2.4.13前景提取示例代码
OpenCV2编译 基于高斯混合模型 #include<fstream> #include<iostream> #include<iostream> #inclu ...
- ubuntu 搞坏了sudoers文件之修复方案
pkexec visudo askubuntu原回答摘抄如下 On a modern Ubuntu system (and many other GNU/Linux distributions), f ...
- Java对象的深拷贝和浅拷贝、集合的交集并集
http://blog.csdn.net/lian_1988/article/details/45970927 http://www.cnblogs.com/yxnchinahlj/archive/2 ...
- Data Validate 之 Data Annotation
什么是Data Annotation ? 如何使用 ? 自定义Validate Attribute EF Db first中使用Data Annotation asp.net MVC中使用Data ...
- spring拦截器 实现应用之性能监控
package cn.ximi.erp.web.common.interceptors; import cn.ximi.core.common.utils.string.StringUtil; imp ...