Javascript must be enabled for the correct page display

Deep Support Vector Machines for Regression Problems

Schutten, M.H. (2013) Deep Support Vector Machines for Regression Problems. Bachelor's Thesis, Artificial Intelligence.

[img]
Preview
Text
DSVM.pdf - Published Version

Download (315kB) | Preview
[img] Text
AkkoordWiering.pdf - Other
Restricted to Repository staff only

Download (40kB)

Abstract

One of the most accurate machine learning algorithms nowadays is the Support Vector machine. Support Vector Machines use kernels in order to project data on the featurespace. We will introduce a new method of machine learning dubbed the Deep Support Vector Machine. Instead of using a kernel, the Deep Support Vector Machine tries to extract features from its input in order to project it on the featurespace. Now instead of using predefined kernels to classify data we are able to make classifications based on the features of a given input vector.

Item Type: Thesis (Bachelor's Thesis)
Supervisor:
Supervisor nameSupervisor E mail
Wiering, M.A.UNSPECIFIED
Degree programme: Artificial Intelligence
Thesis type: Bachelor's Thesis
Language: English
Date Deposited: 15 Feb 2018 07:52
Last Modified: 02 May 2019 11:27
URI: http://fse.studenttheses.ub.rug.nl/id/eprint/10839

Actions (login required)

View Item View Item