| id |
ecaade2016_120 |
| authors |
Takizawa, Atsushi |
| year |
2016 |
| title |
Estimating Potential Event Occurrence Areas in Small Space based on Semi-supervised Learning |
| doi |
https://doi.org/10.52842/conf.ecaade.2016.2.169
|
| source |
Herneoja, Aulikki; Toni Österlund and Piia Markkanen (eds.), Complexity & Simplicity - Proceedings of the 34th eCAADe Conference - Volume 2, University of Oulu, Oulu, Finland, 22-26 August 2016, pp. 169-178 |
| wos |
WOS:000402064400016 |
| summary |
We propose a method for relatively small space that can optimize the size and shape of the neighborhood of an event occurrence spot on a grid space to minimize the classification error using classification by aggregating emerging patterns based on the concept of semi-supervised learning. We apply this method to data of waiting people in the Umeda Underground Mall and show that the proposed method can improve classification accuracy and understandability of classification rules. |
| keywords |
Small space; spatial event; clustering; classification; mixed integer quadratic programing |
| series |
eCAADe |
| email |
|
| full text |
 file.pdf (6,241,615 bytes) |
| references |
Content-type: text/plain
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| last changed |
2022/06/07 07:56 |
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