Beginners Guide to learn Dimension Reduction techniquesintroduction
Brevity is the soul of wit
This powerful quote by William Shakespeare applies well to techniques used in data Science Analytics as well. Intrigued? Allow me to prove it using a short story.In could ', we conducted a data Hackathon (a Data science competition) in DELHI-NCR, India.Register for Data Hackathon 3.0–the Battle of survivalWe gave participants the challenge to
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
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
Ax uses the inventory dimension check to check the inventory dimension in all aspects of the inventory. We know that most of the check tasks are handed over to the classes of the inventmovent series.There are two main tasks for inventory dimension check: 1. Whether the dimension specified by the user exists in the rele
Tags: style blog http OS Io strong data Dimension optimization In the process of SSAs development and design, dimension optimization is very important because it plays a very important role in the process of SSAs analysis service performance optimization. Generally, the first step to optimize the performance of a cube is to view the dimension and observe the de
Recently learned a bit of PHP array of ascending and descending dimension, nonsense less, on the demo.Suppose there is an array before descending, as follows $array = Array (' a ' = = = Array (' b ' = = 1, ' c ' = = = Array (' d ' = = 2, ' E ' + 3) '), ' f ' = = 4, ' g ' = = AR Ray (' H ' =>5));After dimensionality reduction, the following:Descending dimension $array = Array ( ' 0 ' = = a->b->1, ' 1 '
When we are working on database projects, there are only two principles to optimize the data store: one is Data Storage in blocks, which facilitates data dumping and discipline; the other is processing, the speed at which data is provided. This article mainly introduces three Optimizations in Oracle Data freight yard:PartitionOptimization,DimensionOptimization andMaterialized ViewBased on the above two principles, with the help of the concept of data store, list the database optimization measure
The CSS dimension (Dimension) property allows you to control the height and width of an element. Again, it allows you to increase the line spacing.
More examplesSet the height of an elementThis example shows how to set the height of different elements.Set the height of an image using percentagesThis example shows how to set the height of an element using a percent value.Use pixel values to set the wid
/gen_nn_ops.py", line 4640, in Max_poolData_format=data_format, Name=name)File "/home/ys/.local/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _ Apply_op_helperOP_DEF=OP_DEF)File "/home/ys/.local/lib/python2.7/site-packages/tensorflow/python/util/deprecation.py", line 454, in New_funcreturn func (*args, **kwargs)File "/home/ys/.local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 3155, in Create_opOP_DEF=OP_DEF)File "/home/ys/.loca
Original: BI project note creation Time dimension (2)To create a step:
Serial number
Selected properties
Renamed name
Property category
1
DateKey
DateKey
Conventional
2
Month Key
Month Key
Month
3
中文版 Month Name
中文版 Month Name
One month of the year
4
Month Number of year
Month Number of year
Conventional
finite discrete value.Another reason for the poor dispersion value is because of the curse of dimension (Curse of the dimension) because there will be multiple discrete values after the discrete value of the continuous value, so that if the dimension is large, it will result in very many StatesSo that more computation is needed, which is as the
You need to add custom dimension attributes and hierarchies to the latest project. User-defined operations are completed.AmoProcessing implementation and discovering a very difficult problem. I wonder if you have encountered any similar problems in your peers. Please seek help here.
For example, to illustrate my problem, the time dimension provides the user-defined time period division function, such as c
Introduction:
In the machine learning field, dimensionality reduction refers to the use of some ing method to map data points in the original high-dimensional space to the low-dimensional space. The essence of dimensionality reduction is to learn a ing function.F: X-> Y, WhereXIs the expression of the original data point. Currently, most vector expressions are used.YIs a low-dimensional vector expression after data point ing, usuallyYDimension is smallerX(Of course, it is also possible to impr
How to determine the dimension of the php array. The copy code is as follows :? Php *** returns the array dimension * @ param [type] $ arr [description] * @ return [type] [description] * functionarrayLevel ($ arr) {$ alarr:
The code is as follows:
/*** Returns the array dimension.* @ Param [type] $ arr [description]* @ Return [type] [description]*/Function ar
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timestamp. The default value is numeric, because the primary key column is generally of the numerical type. If the types are different, Mondrian needs to know the correct type to generate an SQL statement. For example, a string value will generate a statement that contains single quotes:
Where productsku = '2017-456-aaa'
2. Multi-level structure
A dimension can contain more than one level:
Note that the first level has no name. By def
name calculation can be used to generate descriptive Dimension member names, define other user hierarchies, or specify the names of "(all)" members, to improve user-friendly features of the dimension. You can specify the "all"-level Member names of the Attribute Hierarchy based on the "all"-level Member names of each user hierarchy. In tasks under this topic, a user hierarchy is defined in the "product"
Explanation 1:
Fact tables are data tables combined by a certain field of analysis.The latitude table is a combination of analysis indicators in this field.
Interpretation 2:
To put it simply;A fact table is a transaction table.A dimension table is a basic table.Used to explain the specific content of the keyword latitude in a fact table.
Explanation 3:
Fact data tableThe central table in the data warehouse architecture, which contains the d
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