Opened 15 years ago

Closed 13 years ago

#32 closed enhancement (wontfix)

add sensitivity to SVM

Reported by: Peter Owned by: Peter
Priority: trivial Milestone:
Component: classifier Version: trunk
Keywords: Cc:

Description

Given a training the SVM should be able to tell what inputs are relevant for classification. The sensitivity is defined to be the sum over training samples of the gradient of the output with respect to the input. This is of course kernel dependent. Hence a new function in KernelFunction? must be implemented telling us gradient of the KernelFunction?.

A special case occurs when the kernel is linear, because the gradient is contant and the sum over samples is a waste of time.

Change History (6)

comment:1 Changed 15 years ago by Peter

Milestone: SVM extensionlater

comment:2 Changed 15 years ago by Markus Ringnér

Summary: add senitivity to SVMadd sensitivity to SVM

comment:3 Changed 14 years ago by Peter

Milestone: later0.4

comment:4 Changed 14 years ago by Peter

Status: newassigned

comment:5 Changed 13 years ago by Peter

Milestone: 0.40.5
Status: assignednew

comment:6 Changed 13 years ago by Peter

Milestone: yat 0.5
Resolution: wontfix
Status: newclosed

This is not very useful except in the linear case. (see ticket:51)

Input ranking based on a non-linear classifier is not straightforward.

Note: See TracTickets for help on using tickets.