When we create dimensions in SSAs, it is sometimes possible that one dimension needs to use multiple table fields as dimension attributes, so there is bound to be an association between the multiple tables, but remember that the correlation between the dimension tables and only one cannot have multiple, let's look at an example.Now we have created a
The support vector machine method is based on the VC dimension Theory of statistical learning theory and the minimum structure risk principle.Confidence risk: The classifier classifies the unknown sample and obtains the error. Experiential risk: A well-trained classifier that re-classifies the training samples. That is, sample error structure risk: Confidence risk + empirical risk structure risk minimization is a strategy proposed to prevent overfitti
Foundataions of machine learning: Rademacher complexity and VC-dimension (2)
(1) growth Function)
Before introducing the growth function, let's introduce an example which will help you understand the growth function.
When the input space is $ \ mathbb {r} $, assume that the space is a threshold function, that is, when the input vertex $ x> V $, The point is marked as positive. For example, Figure 1 shows the six assumptions.
Figure 1 threshold functi
Fact tableEach data warehouse contains one or more fact data tables. Fact data tables may contain business sales data, such as data generated by cash registration firms. Fact data tables usually contain a large number of rows. Fact data tables are mainly characterized by digital data (FACTS) that can be summarized to provide relevant units as historical data, each fact table contains an index composed of multiple parts. This index contains the primary key of the foreign key's correlated latitude
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Bi Data Warehouse product database storage
A typical example is to compare a logical business to a cube. The product dimension, time dimension, and location dimension are different coordinate axes, and the intersection of coordinate axes is a specific fact. That is to say, a fact table is an intersection of m
Here's a brief talk of SCD.Put two useful link addresses before you speak. The author's two papers explain what SCD is and how it is appliedHttp://www.cnblogs.com/biwork/p/3363749.htmlHttp://www.cnblogs.com/biwork/p/3371338.htmlSlow changing dimension translation comes down to the slowly changing dimension. It is applied to the loading of dimension table data in
We often encounter this problem in the design of the Data Warehouse: If the dimension has only one attribute in the dimension design, is the choice to create a single dimension for this attribute, or will the attribute of that dimension be placed directly in the fact table as part of the fact table?Suppose there is a
The primary key in a dimension table usually has two choices: the Natural key (Natural key), which is already present in the business system, usually a character-type marker with a certain business meaning, which uniquely flags each of the dimension tablesRecording. Like whatOrganization's code, abbreviations, time tags, and so on. The other is the surrogate key (surrogate key), which is usuallyA numeric va
Abstract
Yes
With the development of computers and the increasing number of data islands in information systems, how to use the data is a problem facing every enterprise.ETLYesexponential Data Extraction(Extract), Data Conversion(Transform)And Data Loading(Loading)And plays a key role in the application of data warehouse.ETLUse these data islands to form a data warehouse,It is an extremely important part in building a data warehouse. Slow change dimen
Fact table
Each data warehouse contains one or more fact data tables. Fact data tables may contain business sales data, such as cash registration transactions.
The generated data, fact data tables usually contain a large number of rows. Fact data tables are mainly characterized by digital data (FACTS) that can be summarized to provide relevant units as historical data, each fact table contains an index composed of multiple parts. This index contains the primary key of the foreign key's correla
A typical example is to compare the logical business to a cube, the product dimension, the time dimension, and the location dimension as different axes, and the intersection of the axes is a detailed fact. This means that the fact table is an intersection of multiple dimension tables. A
Js one-dimensional array, multi-dimensional array and Object Mixed use method, js dimension
The main purpose of this article is to explain the mixed use of JavaScript arrays and objects. Due to the weak check feature of JS, different types of variables can be stored in the JS array at the same time, for example, you can place numbers, strings, characters, objects, and other content in the same array. Objects can also do the same thing. The difference
each horizontal line of the mobile phone screen, 320 pixels in each vertical column, and 320x240 = 76800 pixels.
Dimension sizeThe dimension value defined in XML. A dimension value is a value with a dimension unit, such as 10px, 2in, and 5sp. The following are supported dimensions in Android:DPDensity-independent pixe
A typical example is the logical business compared to cubes, product dimensions, time dimensions, position dimensions, respectively, as different axes. The intersection of axes is a detailed fact. This fact table is a table of intersection points of multiple dimensions. A dimension table is a form of factual analysis.First, the star structure in the database structure is introduced, which maintains the data in a single fact table in the center of the
This article mainly introduces four knowledge points, which is also the content of my lecture.
1.PCA Dimension reduction operation;
PCA expansion pack of Sklearn in 2.Python;
3.Matplotlib subplot function to draw a child graph;
4. Through the Kmeans to the diabetes dataset clustering, and draw a child map.
Previous recommendation:The Python data Mining course. Introduction to installing Python and crawler"Python Data Mining Course" two. Kmeans cluste
(1) Define VC Dimension:The upper limit of the number of dichotomies is the growth function, the upper limit of the growth function is the boundary function:so VC Bound can be changed to write:below we define VC Dimension:for an alternate set of functionsH,VC Dimensionis what it canShatterthe maximum number of dataN. VC Dimension = minimum break point-1. So inVC Boundin which(2N) ^ (k-1)can be replaced by(2N) ^ (VC
On the theoretical concept of slowly changing Dimension slowly changing dimension see Data Warehouse Series-Slow slowly changing dimension (slowly changing Dimension) common three types and prototype design
This article summarizes several ways to realize the slow gradual change di
Prompt: The explanation in this article is more profound. You need to read it with a calm mind!
Preface
At the bottom layer of the IOS interaction model, there is a concept of "space" (specifically, the IOS Space Model), and the most basic attribute of space is three dimensions. Slide depends on the two-dimensional environment of the screen. You can also think about it from the Dimension Perspective. The most common slide operation is to delete short
Introduction
Fact table
The foreign key that stores the measurement value and dimension table.
Dimension Table
Angle and category. Time, region, and status.
Old Method
Select * from order oinner join district d on o. discode = d. discodeinner join address a on o. addressid =. addressidwhere o. createdate> '2014-2-5 'and o. createdate
It is difficult to add conditions when the stored procedure is killed.
Ax has a very good function to hide or display a dimension, such as a warehouse, a warehouse location, and a batch number. Such operations are available in almost all forms that involve services, for example, the sales, purchase order line, inventory log, item quantity, and Other forms can all be set by the inventory-> Dimension Display button. This function is okay in most cases, but sometimes users want t
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