cslt Wiki - 用户贡献 [zh-cn]

130623-rayila

2013-06-24T00:21:32Z

Rayila：以内容“ Weekly Report: Read the literature named Feature Selection via concave Minimization and Support Vector Machines and the book given by teacher . Next Week: Continue...”创建新页面

Weekly Report:

Read the literature named Feature Selection via concave Minimization and Support Vector Machines and the book given by teacher .

Next Week:

Continue to read more literature about sparseSVM .

2013-06-23

2013-06-24T00:08:03Z

Rayila：

[[130623-Fanhu Bie]]

[[130623-mahpirat]]

[[130623-rayila]]

Rayila - 0617

2013-06-17T00:36:48Z

Rayila：以内容“ Weekly Report: Read the literature named 1-norm support vector machines and the book given by teacher . Next Week: Continue to read more literature about sparseSVM .”创建新页面

Weekly Report:

Read the literature named 1-norm support vector machines and the book given by teacher .

Next Week:

Continue to read more literature about sparseSVM .

2013-06-16

2013-06-17T00:28:14Z

Rayila：

[[Fanhu Bie 0616]]

[[rayila - 0617]]

Rayila - 130609

2013-06-09T06:15:16Z

Rayila：以内容“ Weekly Report: To better understand the principles , read some information , mainly read the book given by teacher. Next Week: Read some literature about sparseSVM...”创建新页面

Weekly Report:

To better understand the principles , read some information , mainly read the book given by teacher.

Next Week:

Read some literature about sparseSVM and continue to read the book <Pattern Recognition and Machine Learning> .

2013-06-09

2013-06-09T05:55:50Z

Rayila：

[[Miao Fan - 130609]]

[[rayila - 130609]]

Rayila - 130603

2013-06-03T06:31:10Z

Rayila：

Weekly Report:

Read the information given by the teacher and discussed , understand the problems that do not understand.

Next Week:

But understanding is not enought , continued to see more information

Rayila - 130603

2013-06-03T06:30:55Z

Rayila：以内容“ Weekly Report: Read the information given by the teacher and discussed , understand the problems that do not understand. Next Week: But understanding is not enought...”创建新页面

2013-06-03

2013-06-03T06:16:46Z

Rayila：

[[Linlin Wang - 130603]]

[[Jun Wang - 130603]]

[[Guoyu Tang - 130603]]

[[Mengyuan Zhao - 130603]]

[[Miao Fan - 130603]]

[[rayila - 130603]]

Rayila - 0526

2013-05-27T01:14:35Z

Rayila：

Weekly Report:

Read some material about Sparse SVM and Sparse classification ,and have a initial understanding.

Next Week:

For better understand the principles ,carefully read the information given by the teacher .

Rayila - 0526

2013-05-27T01:14:24Z

Rayila：以内容“ Weekly Report: Read some material about Sparse SVM and Sparse classification ,and have a initial understanding. Next Week: For better understand the principles ,caref...”创建新页面

Weekly Report:
Read some material about Sparse SVM and Sparse classification ,and have a initial understanding.

Next Week:
For better understand the principles ,carefully read the information given by the teacher .

2013-05-26

2013-05-27T00:53:45Z

Rayila：

[[Linlin Wang - 0526]]

[[Fanhu Bie - 0526]]

[[Jun Wag - 0527]]

[[Mengyuan Zhao - 0526]]

[[mahpirat-- 0526]]

[[rayila - 0526]]

Rayila - 130520

2013-05-20T05:29:16Z

Rayila：

Weekly Report:

Running with own data the sparseSVM example of teacher gaves , can probably see that sparseSVM is batter than SVM , but the final result hao not come out.

Used SDA, get 2000,5000... words to calculate its tf value, using MATLAB obtain recognition rate , they have are same results.

Next Week:

To further understanding of sparseSVM , continue to see more material.

Rayila - 130520

2013-05-20T05:27:05Z

Rayila：以内容“ Weekly Report: Running with own data the sparseSVM example of teacher gaves , can probably see that sparseSVM is batter than SVM , but the final result hao not come o...”创建新页面

Weekly Report:

Running with own data the sparseSVM example of teacher gaves , can probably see that sparseSVM is batter than SVM , but the final result hao not come out.

used SDA, get 2000,5000... words to calculate its tf value, using MATLAB obtain recognition rate , they have are same results.

Next Week:

To further understanding of sparseSVM , continue to see more material.

2013-05-20

2013-05-20T05:00:58Z

Rayila：

[[Chenhao Zhang - 130520]]

[[Guoyu Tang - 130520]]

[[Linlin Wang - 130520]]

[[Mengyuan Zhao - 130520]]

[[askar - 130520]]

[[rayila - 130520]]

Rayila - 130512

2013-05-12T01:09:13Z

Rayila：

Weekly Report:

Through the interpretation of the teacher and view some of the information seek for myself and the teacher's given, have a certain understanding of the basic principles of SVM and sparseSVM.

By running the examples given by the teacher, to understand the SVM and sparseSVM difference.

Next Week:

Run with own data to see the results on the basis of the teacher gave the example.

To further understand spaereSVM, continue to view information.

2013-05-12

2013-05-12T00:34:35Z

Rayila：

[[Miao Fan - 130512]]

[[rayila - 130512]]

2013-05-12

2013-05-12T00:34:21Z

Rayila：

[[Miao Fan - 130512]]

[[rayila - 130512]]

2013-05-12

2013-05-12T00:34:06Z

Rayila：

[[Miao Fan - 130512]]
[[rayila - 130512]]

Rayila - 130429

2013-04-28T02:20:14Z

Rayila：以内容“ Weekly Report: Finished the calculate tf-idf-feature . Receive the new assignment: used SDA, get 1000 words to calculate its tf value, using MATLAB obtain recognition...”创建新页面

Weekly Report:

Finished the calculate tf-idf-feature .
Receive the new assignment: used SDA, get 1000 words to calculate its tf value, using MATLAB obtain recognition rate.

Next week:

Continue to calculate tf value and further understanding of the principle of SDA.

2013-04-29

2013-04-28T01:58:56Z

Rayila：

[[Jun Wang - 130429]]

[[Miao Fan - 130429]]

[[Zhiyong Zhang - 130429]]

[[mahpirat - 130429]]

[[Mengyuan Zhao - 130429]]

[[ChenhaoZhao - 130429]]

[[rayila - 130429]]

Rayila -130422

2013-04-22T01:14:31Z

Rayila：

Weekly Report:

First obtain the keyword,and complete to 20 words,40words,60words,80words and 100words into svmfeat,andthen use svm classifier for classification.
these are calculate for tf-feature,also have tf-idf-feature.

next week:

Continue to calculate tf-idf-feature.

Rayila -130422

2013-04-22T01:13:59Z

Rayila：以内容“ Weekly Report: First obtain the keyword,and complete to 20 words,40words,60words,80words and 100words into svmfeat,andthen use svm classifier for classification. the...”创建新页面

2013-04-22

2013-04-22T00:53:26Z

Rayila：

[[Chenhao Zhang - 130421]]

[[Jun Wang - 130421]]

[[Han Qiu - 130421]]

[[Fanhu Bie - 130421]]

[[mahpirat --130422]]

[[Zhiyong Zhang - 130422]]

[[rayila -130422]]

Rayila --130415

2013-04-15T12:44:21Z

Rayila：

Two days Report:

1.Obtain the keyword calculated by df-divergence,idf,tf-divergence,tf-df-divergence,tf-idf-divergence,tf-df-idf-divergence.
2.Gets the 20words from keyword/df-divergence-abs,after that 20words into svmfeat,look it how the result.

Plan for this week:

Continue to get svmfeat for 40words,60words,80words and 100words. and look it how the result for svm.

Rayila --130415

2013-04-15T12:43:29Z

Rayila：以内容“Two days Report 1.Obtain the keyword calculated by df-divergence,idf,tf-divergence,tf-df-divergence,tf-idf-divergence,tf-df-idf-divergence. 2.Gets the 20words from keyw...”创建新页面

Two days Report
1.Obtain the keyword calculated by df-divergence,idf,tf-divergence,tf-df-divergence,tf-idf-divergence,tf-df-idf-divergence.
2.Gets the 20words from keyword/df-divergence-abs,after that 20words into svmfeat,look it how the result.

Plan for this week
Continue to get svmfeat for 40words,60words,80words and 100words. and look it how the result for svm.

2013-04-15

2013-04-15T12:00:01Z

Rayila：

[[Jun Wang - 130414]]

[[Fanhu Bie - 130414]]

[[Han Qiu - 130414]]

[[Linlin Wang - 130415]]

[[Zhongda Xie - 130415]]

[[Chao Liu - 130415]]

[[Cheng Gong - 130415]]

[[Guoyu Tang - 130415]]

[[askar - 130415]]

[[Chenhao Zhang - 130415]]

[[Zhiyong Zhang - 130415]]

[[mahpirat - 130415]]

[[rayila --130415]]