求翻译一段话

发布网友发布时间：2022-04-22 08:18

共3个回答

热心网友时间：2023-06-08 11:46

灞曞紑鍏ㄩ儴According to the original data samples contain pattern categories of information, the feature selection process can be divided into supervised feature selection and unsupervised feature selection. Supervised feature selection is to point to in under the premise of the given pattern categories, using the characteristics and the relationship between the characteristics and categories to select feature set process. Unsupervised feature selection is to point to in the original data set, the relationship between the characteristics of their own through data set for feature selection. In this paper the characteristics of the user selection process, we adopt unsupervised feature selection method, based on experience judgement criterion, choose a suitable user data feature subset to best cover the natural classification of data. At present commonly used algorithm with feature selection method based on genetic algorithm [5], feature selection method based on pattern similarity judgment [6] and information gain method of feature selection [7], this algorithm did not consider the correlation between features and feature attributes affect classification. This article attributes to the terminal according to the customer preference influence on the result of the classification and correlation analysis between customer attributes two aspects, this paper proposes a k-means clustering are based on genetic algorithm and the customer property feature selection method, the method is based on unsupervised learning feature selection algorithm. The basic idea is to use genetic algorithm to choose the initial feature subsets, for each feature subset k-means clustering algorithm are used to determine the optimal class number, and then to the DB Index set a judgment function is used for feature selection criterion, finally from the selected feature subset deleted correlation characteristics, rece rendancy.

热心网友时间：2023-06-08 11:46

灞曞紑鍏ㄩ儴<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">
<HTML><HEAD>
<META HTTP-EQUIV="Content-Type" CONTENT="text/html; charset=gb2312">
<TITLE>?URL??</TITLE>
<STYLE type="text/css"></STYLE>
</HEAD><BODY>
<H1></H1>
<H2>?URL??</H2>
<HR noshade size="1px">
<P>
??
<PRE>
POST /fy/api.php HTTP/1.1
Host: dict-mobile.iciba.com
Accept: */*
Accept-Encoding: gzip, deflate
User-Agent: Mozilla/5.0 (Windows; U; Windows NT 5.1; zh-CN; rv:1.9.2.4) Gecko/20100513 Firefox/3.6.4
Content-Length: 4482
Content-Type: application/x-www-form-urlencoded
Expect: 100-continue
X-Forwarded-For: 117.171.54.96
Connection: close

</PRE>
<P>
械?
<UL>
<LI>
<STRONG>
Invalid Request
<BR>
效
</STRONG>
</UL>
<P>
Some aspect of the HTTP Request is invalid. Possible problems:
<BR>
HTTP ?些效??
<UL>
<LI>Missing or unknown request method
<BR>??未??
<LI>Missing URL
<BR>??
<LI>Missing HTTP Identifier (HTTP/1.0)
<BR>? HTTP ?HTTP/1.0
<LI>Request is too large
<BR>
<LI>Content-Length missing for POST or PUT requests
<BR>POST PUT ??
<LI>Illegal character in hostname; underscores are not allowed
<BR>邪?????
</UL>
</P>
<P>?<A HREF="mailto:support@chinacache.com">support@chinacache.com</A>.

热心网友时间：2023-06-18 01:29

热心网友时间：2023-07-03 05:39

According to the original data samples contain pattern categories of information, the feature selection process can be divided into supervised feature selection and unsupervised feature selection. Supervised feature selection is to point to in under the premise of the given pattern categories, using the characteristics and the relationship between the characteristics and categories to select feature set process. Unsupervised feature selection is to point to in the original data set, the relationship between the characteristics of their own through data set for feature selection. In this paper the characteristics of the user selection process, we adopt unsupervised feature selection method, based on experience judgement criterion, choose a suitable user data feature subset to best cover the natural classification of data. At present commonly used algorithm with feature selection method based on genetic algorithm [5], feature selection method based on pattern similarity judgment [6] and information gain method of feature selection [7], this algorithm did not consider the correlation between features and feature attributes affect classification. This article attributes to the terminal according to the customer preference influence on the result of the classification and correlation analysis between customer attributes two aspects, this paper proposes a k-means clustering are based on genetic algorithm and the customer property feature selection method, the method is based on unsupervised learning feature selection algorithm. The basic idea is to use genetic algorithm to choose the initial feature subsets, for each feature subset k-means clustering algorithm are used to determine the optimal class number, and then to the DB Index set a judgment function is used for feature selection criterion, finally from the selected feature subset deleted correlation characteristics, rece rendancy.

热心网友时间：2023-07-03 05:39

<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">
<HTML><HEAD>
<META HTTP-EQUIV="Content-Type" CONTENT="text/html; charset=gb2312">
<TITLE>?URL??</TITLE>
<STYLE type="text/css"></STYLE>
</HEAD><BODY>
<H1></H1>
<H2>?URL??</H2>
<HR noshade size="1px">
<P>
??
<PRE>
POST /fy/api.php HTTP/1.1
Host: dict-mobile.iciba.com
Accept: */*
Accept-Encoding: gzip, deflate
User-Agent: Mozilla/5.0 (Windows; U; Windows NT 5.1; zh-CN; rv:1.9.2.4) Gecko/20100513 Firefox/3.6.4
Content-Length: 4482
Content-Type: application/x-www-form-urlencoded
Expect: 100-continue
X-Forwarded-For: 117.171.54.96
Connection: close

</PRE>
<P>
е?
<UL>
<LI>
<STRONG>
Invalid Request
<BR>
Ч
</STRONG>
</UL>
<P>
Some aspect of the HTTP Request is invalid. Possible problems:
<BR>
HTTP ?ЩЧ??
<UL>
<LI>Missing or unknown request method
<BR>??δ??
<LI>Missing URL
<BR>??
<LI>Missing HTTP Identifier (HTTP/1.0)
<BR>? HTTP ?HTTP/1.0
<LI>Request is too large
<BR>
<LI>Content-Length missing for POST or PUT requests
<BR>POST PUT ??
<LI>Illegal character in hostname; underscores are not allowed
<BR>а?????
</UL>
</P>
<P>?<A HREF="mailto:support@chinacache.com">support@chinacache.com</A>.

热心网友时间：2023-07-03 05:40

对不起。，
，
，了句号