A low dimensional categorical data transform based on Feature Combination
碩士 === 國立臺灣科技大學 === 資訊工程系 === 105 === This research focuses on how to transform the categorical data into numerical data efficiently. Although there are plenty of encoders for processing the categorical data, there are two severe defects of high informaiton with high dimension or low dimension with...
Main Authors: | Wie-Zhih Lin, 林威志 |
---|---|
Other Authors: | Wei-Chung Teng |
Format: | Others |
Language: | zh-TW |
Published: |
2017
|
Online Access: | http://ndltd.ncl.edu.tw/handle/7k2q7u |
Similar Items
-
Clinical Features of Psychotic Disorders: Comparing Categorical and Dimensional Models
by: Caitlin Ravichandran, et al.
Published: (2021-03-01) -
THE EFFECT OF BINARY DATA TRANSFORMATION IN CATEGORICAL DATA CLUSTERING
by: Jana Cibulková, et al.
Published: (2019-06-01) -
Graph Clustering for Categorical Data
by: Chen, Wei-Shiang, et al.
Published: (2018) -
Combining Classifiers for Chinese Text Categorization
by: Hung-Ru Lin, et al.
Published: (2000) -
Regularized Feature Selection in Categorical PLS for Multicollinear Data
by: Tahir Mehmood
Published: (2021-01-01)