TY - GEN
T1 - Multi-dimension projection for non-linear data via spearman correlation analysis (MD-SCA)
AU - Khokhar, Muhammad Saddam
AU - Cheng, Keyang
AU - Ayoub, Misbah
AU - Zakria, Z.
AU - Eric, Lubamba Kasangu
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - This paper introduces an algorithm of multidimensional informative projection or view of multiple variable and more than two random variables via Spearman correlation analysis (SCA). The proposed algorithm is an extension of Spearman correlation analysis to extract linear or nonlinear information of projections through pairwise correlation analysis. These multi-dimensional informative projections used as common patterns in pattern recognition application. The proposed algorithm extends SCA through linear algebraic solution for the optimization problem, the problem of dual representation of high multi-dimensional data, and structural dilemma issues along with deep learning model. Additionally, the proposed method decreases the quadratic algorithm complexity among linear and non-linear data through Spearman rank ability. The demonstration of proposed approached performs on two-bench mark data set: Face96 and Yale Face Database.
AB - This paper introduces an algorithm of multidimensional informative projection or view of multiple variable and more than two random variables via Spearman correlation analysis (SCA). The proposed algorithm is an extension of Spearman correlation analysis to extract linear or nonlinear information of projections through pairwise correlation analysis. These multi-dimensional informative projections used as common patterns in pattern recognition application. The proposed algorithm extends SCA through linear algebraic solution for the optimization problem, the problem of dual representation of high multi-dimensional data, and structural dilemma issues along with deep learning model. Additionally, the proposed method decreases the quadratic algorithm complexity among linear and non-linear data through Spearman rank ability. The demonstration of proposed approached performs on two-bench mark data set: Face96 and Yale Face Database.
KW - Linear algebraic formulation
KW - Multi-dimensional projection
KW - Spearman correlation analysis
KW - Squeezenet
UR - http://www.scopus.com/inward/record.url?scp=85081626873&partnerID=8YFLogxK
U2 - 10.1109/ICICT47744.2019.9001973
DO - 10.1109/ICICT47744.2019.9001973
M3 - Conference Proceeding
AN - SCOPUS:85081626873
SN - 978-1-7281-2335-6
T3 - 2019 8th International Conference on Information and Communication Technologies, ICICT 2019
SP - 14
EP - 18
BT - 2019 8th International Conference on Information and Communication Technologies, ICICT 2019
A2 - Mahmood, Tariq
A2 - Khoja, Shakeel
A2 - Ghani, Sayeed
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th International Conference on Information and Communication Technologies, ICICT 2019
Y2 - 16 November 2019 through 17 November 2019
ER -