Decentralization has a negative value

1.

Decentralization is a form of social relations and content proction formed in the development of the Internet. It is a new type of network content proction process relative to "centralization"

decentralizing is not to do without the center, but to let the nodes freely choose and decide the center. In short, centralization means that the center determines the node. The node must depend on the center, and the node cannot survive without the center. In a decentralized system, anyone is a node, and anyone can be a center. Any center is not permanent, but phased, and no center is mandatory for nodes

extended materials:

content

from the perspective of Internet development, decentralization is the form of social relationship and content proction formed in the process of Internet development, and is a new type of network content proction process relative to "centralization"

compared with the early Internet (WEB 1.0) era, today's Internet (Web 2.0) content is no longer proced by professional websites or specific groups of people, but is the result of the joint participation and equal power of all Internet users. Anyone can express their views or create original content on the Internet to proce information together

with the diversification of network service forms, the decentralized network model becomes more and more clear and possible. After the rise of Web2.0, the services provided by Wikipedia, Flickr, blogger and other network service providers are decentralized. Any participant can submit content, and Internet users can create or contribute content together

after that, with the emergence of more simple and easy-to-use decentralized network services, the characteristics of Web2.0 become more and more obvious. For example, the birth of services more suitable for ordinary Internet users, such as twitter and Facebook, makes it easier and more diversified to proce or contribute content to the Internet, thus enhancing the enthusiasm of Internet users to participate in the contribution and recing the threshold of procing content. Eventually, every netizen becomes a tiny and independent information provider, making the Internet more flat and content proction more diversified

2. According to Hou Jietai: the so-called centralization refers to subtracting the mean value of a variable from its expected value. For sample data, each observation value of a variable is subtracted from the sample average value of the variable, and the transformed variable is centralized
for your question, subtract the mean from each measurement.

3. In the process of decentralization, it is true that only our responsible attitude can be exchanged for a better one. Evaluation.

4.

De flow means that all social resources can be aggregated and distributed with one click

in a system with many nodes, each node has a high degree of autonomy. Nodes can connect with each other freely to form a new connection unit. Any node may become the stage center, but it does not have the mandatory central control function. The influence between nodes will form a nonlinear causal relationship through the network

This kind of open, flat and equal system phenomenon or structure is called decentralization

extended materials:

compared with the previous Internet (WEB 1.0) era, today's Internet (Web 2.0) content is no longer proced by professional websites or specific groups, but by the participation of the whole Internet users and the creation of equal power levels. Anyone can express their views on the Internet or create original content to proce information together

with the diversification of network service shape, the decentralized network model becomes more and more clear and possible. After the rise of Web2.0, the services provided by Wikipedia, Flickr, blogger and other network service providers are decentralized. Any participant can submit content, and Internet users can create or contribute content together

5.

In a system with many nodes, each node has a high degree of autonomy. Nodes can connect freely to each other to form a new connection unit. Any node may become the stage center, but it does not have the mandatory central control function. The influence between nodes will form nonlinear causality through the network. This open, flat and equal system phenomenon or structure is called decentralization

with the deepening of the interaction between subject and object, the constant balance of cognitive function and the continuous improvement of cognitive structure, the indivial can be released from the egocentric state, which is called decentralization< br />

6. After the interview in recent days, I found that data dimensionality rection is widely used or indispensable in the instry. Therefore, this aspect needs to be focused on. Today, I will summarize the data dimensionality rection, including other people's achievements. Here I would like to thank them for their contents

method
has multiple perspectives on the role of data dimensionality rection. Wu Enda said in his video that dimensionality rection is used for data compression to rece noise and prevent slow running and small memory; When it is reced to 2 or 3 dimensions, it can be visualized for data analysis; Don't use dimension rection to prevent over fitting. It's easy to remove important features related to tags. But why data need to be compressed, in addition to occupying memory, is there any other reason - "dimension disaster" problem: the higher the dimension, the more sparse the distribution of your data on each feature dimension, which is basically disastrous for machine learning algorithms. The final result may be that each sample has its own characteristics, which can not form a unified feature to distinguish positive cases from negative cases. There is another case, when the feature is more than the sample size, some classification algorithms (SVM) are invalid, which is related to the principle of classification algorithm<

data dimension rection method:
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linear dimensionality rection method:
principal component analysis (PCA) and discriminant analysis (LDA)
understanding of PCA:
1. PCA can be understood as the projection of high-dimensional data to low-dimensional data, and make the projection error minimum. It's an unsupervised method
2. It can also be understood as coordinate rotation and translation (corresponding to coordinate transformation and decentralization), so that the n-dimensional space can be analyzed in n-1 dimension, and the characteristics of small variance (small variance, small uncertainty, small amount of information)
3. Derivation of PCA
4. Connection between PCA and SVD
(Understanding PCA from the perspective of matrix decomposition)
5. Application of PCA dimension rection
6 Disadvantages of PCA:
(1) PCA is a linear dimensionality rection method, sometimes the nonlinear relationship between data is very important, when we use PCA, we will get very poor results. Next, we introce PCA of kernel method
(2) principal component analysis is more effective only when the sample points obey Gaussian distribution
(3) cost sensitive PCA (cspca) can be used to rece the dimension of imbalanced data.
(4) the size of feature roots determines how much information we are interested in. In other words, small feature roots often represent noise, but in fact, the projection to smaller feature roots may also include the data we are interested in
(5) the directions of eigenvectors are orthogonal, which makes PCA vulnerable to outlier
(6) it is difficult to explain the results. For example, in the establishment of linear regression model (linear regression model) analysis of dependent variables

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8.

Decentralization means no center

extended meaning: with the deepening of the interaction between subject and object, the continuous balance of cognitive function and the continuous improvement of cognitive structure, the indivial can be released from the egocentric state, which Piaget calls decentralization

This kind of open, flat and equal system phenomenon or structure is called decentralization

extended data:

in a system with many nodes, each node has the characteristics of high degree of autonomy. Nodes can connect freely to each other to form a new connection unit. Any node may become the stage center, but it does not have the mandatory central control function. The influence between nodes will form nonlinear causality through the network. This open, flat and equal system phenomenon or structure is called decentralization

with the deepening of the interaction between subject and object, the constant balance of cognitive function and the continuous improvement of cognitive structure, the indivial can be released from the egocentric state, which is called decentralization