Recent changes to RankLib

RankLib modified by Michael Zarozinski

Michael Zarozinski — Wed, 16 Oct 2019 15:36:05 -0000

--- v17
+++ v18
@@ -50,11 +50,6 @@

 # #

-#### Older Versions ####
-Older versions of RankLib (before it moved into the Lemur Project) can be found [here](http://people.cs.umass.edu/~vdang/ranklib.html).
-
-# #
-
 #### License ####
 RankLib is available under [BSD license](http://people.cs.umass.edu/~vdang/ranklib_license.html).

RankLib modified by Van Dang

Van Dang — Sat, 05 Oct 2013 00:58:52 -0000

--- v16
+++ v17
@@ -68,4 +68,4 @@
 \[5\] Q. Wu, C.J.C. Burges, K. Svore and J. Gao. Adapting Boosting for Information Retrieval Measures. Journal of Information Retrieval, 2007.
 \[6\] J.H. Friedman. Greedy function approximation: A gradient boosting machine. Technical Report, IMS Reitz Lecture, Stanford, 1999; see also Annals of Statistics, 2001.
 \[7\] Z. Cao, T. Qin, T.Y. Liu, M. Tsai and H. Li. Learning to Rank: From Pairwise Approach to Listwise Approach. ICML 2007. 
-\[8\] J.H. Friedman. Greedy function approximation: A gradient boosting machine. Annals of Statistics 29: 1189–1232, 1999.
+\[8\] L. Breiman. Random Forests. Machine Learning 45 (1): 5–32, 2001.

RankLib modified by Van Dang

Van Dang — Wed, 14 Aug 2013 17:48:19 -0000

RankLib modified by Van Dang

Van Dang — Wed, 14 Aug 2013 17:21:42 -0000

--- v14
+++ v15
@@ -46,7 +46,7 @@
 # #

 #### Community Contribution ####
-If you want to contribute (ideas, codes, etc.) to make RankLib better, let us know in the [community contribution forum](https://sourceforge.net/p/lemur/discussion/communitycontribution/).
+If you want to contribute (ideas, codes, etc.) to make RankLib better, let me know in the [community contribution forum](https://sourceforge.net/p/lemur/discussion/communitycontribution/).

 # #

RankLib modified by Van Dang

Van Dang — Wed, 14 Aug 2013 17:19:38 -0000

--- v13
+++ v14
@@ -55,6 +55,11 @@

 # #

+#### License ####
+RankLib is available under [BSD license](http://people.cs.umass.edu/~vdang/ranklib_license.html).
+
+# #
+
 #### References ####
 \[1\]  C.J.C. Burges, T. Shaked, E. Renshaw, A. Lazier, M. Deeds, N. Hamilton and G. Hullender. Learning to rank using gradient descent. In Proc. of ICML, pages 89-96, 2005.
 \[2\] Y. Freund, R. Iyer, R. Schapire, and Y. Singer. An efficient boosting algorithm for combining preferences. The Journal of Machine Learning Research, 4: 933-969, 2003.

RankLib modified by Van Dang

Van Dang — Wed, 14 Aug 2013 15:29:55 -0000

--- v12
+++ v13
@@ -1,6 +1,10 @@
 ## RankLib ##

 -----
+
+# #
+
+#### Overview ####

 RankLib is a library of learning to rank algorithms. Currently eight popular algorithms have been implemented: 

@@ -42,7 +46,7 @@
 # #

 #### Community Contribution ####
-If you want to contribute (ideas, codes, etc) to make Ranklib better, let us know in the [community contribution forum](https://sourceforge.net/p/lemur/discussion/communitycontribution/).
+If you want to contribute (ideas, codes, etc.) to make RankLib better, let us know in the [community contribution forum](https://sourceforge.net/p/lemur/discussion/communitycontribution/).

 # #

RankLib modified by Van Dang

Van Dang — Wed, 14 Aug 2013 15:22:24 -0000

--- v11
+++ v12
@@ -31,6 +31,26 @@

 # #

+#### Bug Report & Feature Request ####
+Use the sourceforge toolbar  right above this page: "Tickets" -> "Bugs" and "Feature Requests".
+
+# #
+
+#### General Questions & Discussions ####
+Use the [discussion forum](https://sourceforge.net/p/lemur/discussion/ranklib/).
+
+# #
+
+#### Community Contribution ####
+If you want to contribute (ideas, codes, etc) to make Ranklib better, let us know in the [community contribution forum](https://sourceforge.net/p/lemur/discussion/communitycontribution/).
+
+# #
+
+#### Older Versions ####
+Older versions of RankLib (before it moved into the Lemur Project) can be found [here](http://people.cs.umass.edu/~vdang/ranklib.html).
+
+# #
+
 #### References ####
 \[1\]  C.J.C. Burges, T. Shaked, E. Renshaw, A. Lazier, M. Deeds, N. Hamilton and G. Hullender. Learning to rank using gradient descent. In Proc. of ICML, pages 89-96, 2005.
 \[2\] Y. Freund, R. Iyer, R. Schapire, and Y. Singer. An efficient boosting algorithm for combining preferences. The Journal of Machine Learning Research, 4: 933-969, 2003.

RankLib modified by Van Dang

Van Dang — Wed, 14 Aug 2013 14:56:46 -0000

--- v10
+++ v11
@@ -22,6 +22,12 @@
 * [Download & Install](https://sourceforge.net/p/lemur/wiki/RankLib%20Installation/)
 * [File Format](https://sourceforge.net/p/lemur/wiki/RankLib%20File%20Format/)
 * [How to use](https://sourceforge.net/p/lemur/wiki/RankLib%20How%20to%20use/)
+    * [Cmd-line parameters](https://sourceforge.net/p/lemur/wiki/RankLib%20How%20to%20use/)
+    * [Train models from held-out data](https://sourceforge.net/p/lemur/wiki/RankLib%20How%20to%20use#training)
+    * [k-fold cross validation](https://sourceforge.net/p/lemur/wiki/RankLib%20How%20to%20use#kcv)
+    * [Evaluate pre-trained models](https://sourceforge.net/p/lemur/wiki/RankLib%20How%20to%20use#eval)
+    * [Compare models](https://sourceforge.net/p/lemur/wiki/RankLib%20How%20to%20use#compare_models)
+    * [Use pre-trained models for ranking](https://sourceforge.net/p/lemur/wiki/RankLib%20How%20to%20use#ranking)

 # #

RankLib modified by Van Dang

Van Dang — Wed, 14 Aug 2013 14:22:38 -0000

--- v9
+++ v10
@@ -1,4 +1,6 @@
 ## RankLib ##
+
+-----

 RankLib is a library of learning to rank algorithms. Currently eight popular algorithms have been implemented:

RankLib modified by Van Dang

Van Dang — Wed, 14 Aug 2013 14:17:43 -0000

--- v8
+++ v9
@@ -1,4 +1,4 @@
-# RankLib #
+## RankLib ##

 RankLib is a library of learning to rank algorithms. Currently eight popular algorithms have been implemented: 

@@ -13,15 +13,17 @@

 It also implements many retrieval metrics as well as provides many ways to carry out evaluation.

+# #

-### Getting Started ###
+#### Getting Started ####

-* [RankLib Installation]
-* [RankLib File Format]
-* [RankLib How to use]
+* [Download & Install](https://sourceforge.net/p/lemur/wiki/RankLib%20Installation/)
+* [File Format](https://sourceforge.net/p/lemur/wiki/RankLib%20File%20Format/)
+* [How to use](https://sourceforge.net/p/lemur/wiki/RankLib%20How%20to%20use/)

+# #

-### References ###
+#### References ####
 \[1\]  C.J.C. Burges, T. Shaked, E. Renshaw, A. Lazier, M. Deeds, N. Hamilton and G. Hullender. Learning to rank using gradient descent. In Proc. of ICML, pages 89-96, 2005.
 \[2\] Y. Freund, R. Iyer, R. Schapire, and Y. Singer. An efficient boosting algorithm for combining preferences. The Journal of Machine Learning Research, 4: 933-969, 2003.
 \[3\] J. Xu and H. Li. AdaRank: a boosting algorithm for information retrieval. In Proc. of SIGIR, pages 391-398, 2007.