The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
데이터 포인트의 병렬 이동 하에서 음이 아닌 행렬 인수분해 결과에 대한 속성을 고려합니다. 원본 데이터 포인트의 구름 모양과 벡터에 평행하게 이동하는 데이터 포인트의 모양은 동일합니다. 따라서 두 데이터 포인트의 기본 벡터에 대한 계수도 분류 관점에서 동일해야 하는 경우가 있습니다. 우리는 데이터 포인트의 변환에 따라 그러한 불변 속성에 대한 필요조건과 충분조건을 보여줍니다.
Hideyuki IMAI
Hokkaido University
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부
Hideyuki IMAI, "Shift Invariance Property of a Non-Negative Matrix Factorization" in IEICE TRANSACTIONS on Fundamentals,
vol. E103-A, no. 2, pp. 580-581, February 2020, doi: 10.1587/transfun.2019EAL2121.
Abstract: We consider a property about a result of non-negative matrix factorization under a parallel moving of data points. The shape of a cloud of original data points and that of data points moving parallel to a vector are identical. Thus it is sometimes required that the coefficients to basis vectors of both data points are also identical from the viewpoint of classification. We show a necessary and sufficient condition for such an invariance property under a translation of the data points.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2019EAL2121/_p
부
@ARTICLE{e103-a_2_580,
author={Hideyuki IMAI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Shift Invariance Property of a Non-Negative Matrix Factorization},
year={2020},
volume={E103-A},
number={2},
pages={580-581},
abstract={We consider a property about a result of non-negative matrix factorization under a parallel moving of data points. The shape of a cloud of original data points and that of data points moving parallel to a vector are identical. Thus it is sometimes required that the coefficients to basis vectors of both data points are also identical from the viewpoint of classification. We show a necessary and sufficient condition for such an invariance property under a translation of the data points.},
keywords={},
doi={10.1587/transfun.2019EAL2121},
ISSN={1745-1337},
month={February},}
부
TY - JOUR
TI - Shift Invariance Property of a Non-Negative Matrix Factorization
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 580
EP - 581
AU - Hideyuki IMAI
PY - 2020
DO - 10.1587/transfun.2019EAL2121
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E103-A
IS - 2
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - February 2020
AB - We consider a property about a result of non-negative matrix factorization under a parallel moving of data points. The shape of a cloud of original data points and that of data points moving parallel to a vector are identical. Thus it is sometimes required that the coefficients to basis vectors of both data points are also identical from the viewpoint of classification. We show a necessary and sufficient condition for such an invariance property under a translation of the data points.
ER -