-
Notifications
You must be signed in to change notification settings - Fork 0
/
readme.txt
47 lines (37 loc) · 2.44 KB
/
readme.txt
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
This package provides an implementation of the TopPush algorithm proposed in [1].
We provide a demo implementation of TopPush, and develop this package using MATLAB as well
as C-mex (for the projection step). The purpose of this package is to show the effectiveness of
TopPush, and we believe that better efficiency can be obtained by sophisticated coding tricks.
______________________________________________________________________________________
---- * Manual * ----------------------------------------------------------------------
The main algorithm is given in topPush.m, whose manual is as following:
Syntax:
w = topPush(X, y, opt)
Description:
topPush takes,
X - the instance matrix, each row is an instance
y - the labels for each instance (+1 / -1)
opt - the structure of topPush training setting where
.lambda - regularization parameter (default: 1)
.maxIter - maximum number of iterations (defalut: 10000)
.tol - precision parameter (default: 10^-4)
.debug - the indictor for debugging (default: false)
(true for displaying some inner status)
and returns,
w - learnt linear ranking model
_________________________________________________________________________________________
----- * DEMO * --------------------------------------------------------------------------
A demo script named 'demo_topPush.m' is provided. It runs topPush on the spambase dataset
_________________________________________________________________________________________
---- * Projection * ---------------------------------------------------------------------
We implement the projection step (see [1] for details) using C and mex.
epne.c - the C mex-file codes for the projection step
epne.mexw64 - the complied mex file on Windows (64-bit)
If you want to run this code on other platforms, please complie 'epne.c' using mex.
_________________________________________________________________________________________
---- * Attention* -----------------------------------------------------------------------
This package was developed by Mr. Nan Li ([email protected]). For any problem concerning
the codes, please feel free to contact Mr. Li.
Reference:
[1] N. Li, R. Jin and Z.-H. Zhou. Top Rank Optimization in Linear Time. In NIPS-2014.
(Long version: CoRR, abs/1410.1462 | http://arxiv.org/abs/1410.1462)