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
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
|
Supervised Classification
=========================
Every classifier must be initialized with a specific set of
parameters. Two distinct methods are deployed for the *training*
(:meth:`compute()`) and the *testing* (:meth:`predict`)
phases. Whenever possible, the real valued prediction is stored in the
*realpred* variable.
Support Vector Machines (SVMs)
------------------------------
.. autoclass:: mlpy.Svm
:members:
.. note::
For *tr* kernel (Terminated Ramp Kernel) see [Merler06]_.
K Nearest Neighbor (KNN)
------------------------
.. autoclass:: mlpy.Knn
:members:
Fisher Discriminant Analysis (FDA)
----------------------------------
Described in [Mika01]_.
.. autoclass:: mlpy.Fda
:members:
Spectral Regression Discriminant Analysis (SRDA)
------------------------------------------------
Described in [Cai08]_.
.. autoclass:: mlpy.Srda
:members:
Penalized Discriminant Analysis (PDA)
-------------------------------------
Described in [Ghosh03]_.
.. autoclass:: mlpy.Pda
:members:
Diagonal Linear Discriminant Analysis (DLDA)
--------------------------------------------
.. autoclass:: mlpy.Dlda
:members:
.. [Vapnik95] V Vapnik. The Nature of Statistical Learning Theory. Springer-Verlag, 1995.
.. [Cristianini] N Cristianini and J Shawe-Taylor. An introduction to support vector machines. Cambridge University Press.
.. [Merler06] S Merler and G Jurman. Terminated Ramp - Support Vector Machine: a nonparametric data dependent kernel. Neural Network, 19:1597-1611, 2006.
.. [Nasr09] R. Nasr, S. Swamidass, and P. Baldi. Large scale study of multiplemolecule queries. Journal of Cheminformatics, vol. 1, no. 1, p. 7, 2009.
.. [Mika01] S Mika and A Smola and B Scholkopf. An improved training algorithm for kernel fisher discriminants. Proceedings AISTATS 2001, 2001.
.. [Cristianini02] N Cristianini, J Shawe-Taylor and A Elisseeff. On Kernel-Target Alignment. Advances in Neural Information Processing Systems, Volume 14, 2002.
.. [Cai08] D Cai, X He, J Han. SRDA: An Efficient Algorithm for Large-Scale Discriminant Analysis. Knowledge and Data Engineering, IEEE Transactions on Volume 20, Issue 1, Jan. 2008 Page(s):1 - 12.
.. [Ghosh03] D Ghosh. Penalized discriminant methods for the classification of tumors from gene expression data. Biometrics on Volume 59, Dec. 2003 Page(s):992 - 1000(9).
|
