TY - GEN
T1 - Features Spaces with Reduced Variables Based on Nearest Neighbor Relations and Their Inheritances
AU - Ishii, Naohiro
AU - Iwata, Kazunori
AU - Mukai, Naoto
AU - Odagiri, Kazuya
AU - Matsuo, Tokuro
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - Generation of useful variables in the features spaces is an important issue throughout the neural networks, the machine learning and artificial intelligence for their efficient and discriminative computations. In this paper, the nearest neighbor relations are proposed for the minimal generation and the reduced variables for the feature spaces. First, the nearest neighbor relations are shown to be minimal independent and inherited for the construction of the feature space. For the analysis, convex cones are made of the nearest neighbor relations, which are independent vectors for the generation of the reduced variables. Then, edges of convex cones are compared for the discrimination of variables. Finally, feature spaces with the reduced variables based on the nearest neighbor relations are shown to be useful for the real documents classification.
AB - Generation of useful variables in the features spaces is an important issue throughout the neural networks, the machine learning and artificial intelligence for their efficient and discriminative computations. In this paper, the nearest neighbor relations are proposed for the minimal generation and the reduced variables for the feature spaces. First, the nearest neighbor relations are shown to be minimal independent and inherited for the construction of the feature space. For the analysis, convex cones are made of the nearest neighbor relations, which are independent vectors for the generation of the reduced variables. Then, edges of convex cones are compared for the discrimination of variables. Finally, feature spaces with the reduced variables based on the nearest neighbor relations are shown to be useful for the real documents classification.
KW - Convex cones
KW - Independent vectors
KW - Inheritance of the relation
KW - Nearest neighbor relation
UR - https://www.scopus.com/pages/publications/85115123351
UR - https://www.scopus.com/pages/publications/85115123351#tab=citedBy
U2 - 10.1007/978-3-030-85030-2_7
DO - 10.1007/978-3-030-85030-2_7
M3 - Conference contribution
AN - SCOPUS:85115123351
SN - 9783030850296
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 77
EP - 88
BT - Advances in Computational Intelligence - 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, Proceedings
A2 - Rojas, Ignacio
A2 - Joya, Gonzalo
A2 - Catala, Andreu
PB - Springer Science and Business Media Deutschland GmbH
T2 - 16th International Work-Conference on Artificial Neural Networks, IWANN 2021
Y2 - 16 June 2021 through 18 June 2021
ER -