880.txt

This complete matlab for neural network

发信人: GzLi (笑梨), 信区: DataMining
标  题: [合集]学习数据挖掘之前要修什么课？？
发信站: 南京大学小百合站 (Wed Sep 11 12:42:44 2002), 站内信件

softgenius (我爱linux) 于Wed Sep  4 15:52:20 2002)
提到：

我是外系的学生，不懂的问。
一般考试是如何考阿？？？

strawman (独上江楼思渺然) 于Wed Sep  4 16:03:49 2002提到：

知道一些数据库的知识，还有数理统计的知识，我想就可以了吧。
当然也要看教材的深浅了。


sinokdd (KDD in China) 于Thu Sep  5 12:38:37 2002)
提到：


I donot think you need to know Database, actually the last several
chapters in Prof. Han's book can be taken as the introduction of
data mining techniques, and after that you can read 
Machine Learning by Tom Mitchell, then you can read some papers for
the topic that you are interested in, for example, C45, clsutering,
etc.


jimo (寂寞) 于Thu Sep  5 17:40:50 2002提到：

关联规则就不需要太多机器学习的东西



sinokdd (KDD in China) 于Fri Sep  6 08:14:45 2002)
提到：


Yeah, but data mining is not association rule or sequential pattern only.
If you only know AR or SP, I am sure there is very little thing
you can do for data mining.
And actually data mining is borrowed from statistics, and of course you can
say that AR is nothing to do with statistics.
The definition of KDD is the process of pattenr discovery from large data,
the mostly used techiques are from machine learning and statistics. And now
people donot care what technology you use in mining, but if you can get some

patterns, not the original data itself, then you can call the process as
data mining.


jimo (寂寞) 于Fri Sep  6 12:09:19 2002提到：

呵呵   ar 里的sampling 和统计还是有关系的



helloboy (hello) 于Sat Sep  7 17:01:15 2002提到：

Sampling is a process which take a small part of data from origin dataset.
Statistic is different.It use maths model to evaluate data.



fervvac (高远) 于Sun Sep  8 00:36:06 2002提到：

there are theories about "sampling", which was built on top of statistics
stuffs.



helloboy (hello) 于Sun Sep  8 08:24:04 2002提到：

So sampling is based on statistics. right?


fervvac (高远) 于Sun Sep  8 18:28:40 2002提到：

Yes, you can say so.

In fact, if you look at the use of sampling in database literatures, much of
the paper is used to derive the (probabilistic) bound.