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Spa: Signflip Parallel Analysis to Optimize the Number of Pcs in Two-Dimensional Pca

https://doi.org/10.2139/ssrn.4831597
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/bf02289447openalex-extracted
A Rationale and Test for the Number of Factors in Factor Analysis
inferredcites →https://doi.org/10.1016/j.isprsjprs.2014.04.006openalex-extracted
Novel Folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing
inferredcites →https://doi.org/10.1049/cit2.12283openalex-extracted
Feature extraction and learning approaches for cancellable biometrics: A survey
inferredcites →https://doi.org/10.1080/01621459.2026.2719861openalex-extracted
Selecting the number of components in PCA via random signflips
inferredcites →https://doi.org/10.1080/02564602.2020.1740615openalex-extracted
PCA-based Feature Reduction for Hyperspectral Remote Sensing Image Classification
inferredcites →https://doi.org/10.1093/biomet/asr074openalex-extracted
Factor profiled sure independence screening
inferredcites →https://doi.org/10.1109/34.927464openalex-extracted
From few to many: illumination cone models for face recognition under variable lighting and pose
inferredcites →https://doi.org/10.1109/access.2019.2904145openalex-extracted
A Hybrid Feature Extraction Method With Regularized Extreme Learning Machine for Brain Tumor Classification
inferredcites →https://doi.org/10.1109/cvpr.1991.139758openalex-extracted
Face recognition using eigenfaces
inferredcites →https://doi.org/10.1109/icasert.2019.8934543openalex-extracted
Implementation of Principal Component Analysis on Masked and Non-masked Face Recognition
inferredcites →https://doi.org/10.1109/icpr.2000.906203openalex-extracted
Eigenhill vs. eigenface and eigenedge
inferredcites →https://doi.org/10.1109/tap.2024.3349778openalex-extracted
Space-Time-Coding Digital Metasurface Element Design Based on State Recognition and Mapping Methods With CNN-LSTM-DNN
inferredcites →https://doi.org/10.1109/tmm.2020.2976573openalex-extracted
Automated Colorization of a Grayscale Image With Seed Points Propagation
inferredcites →https://doi.org/10.1109/tpami.2004.1261097openalex-extracted
Two-dimensional pca: a new approach to appearance-based face representation and recognition
inferredcites →https://doi.org/10.1145/3637441openalex-extracted
Multiple Pseudo-Siamese Network with Supervised Contrast Learning for Medical Multi-modal Retrieval
inferredcites →https://doi.org/10.1155/2019/4253641openalex-extracted
Automated Breast Cancer Diagnosis Based on Machine Learning Algorithms
inferredcites →https://doi.org/10.1162/rest_a_00043openalex-extracted
Determining the Number of Factors from Empirical Distribution of Eigenvalues
inferredcites →https://doi.org/10.1201/9781420067972-10openalex-extracted
Multivariate Data Analysis
inferredcites →https://doi.org/10.1207/s15327906mbr1203_2openalex-extracted
A Comprehensive Trial Of The Scree And Kg Criteria For Determining The Number Of Factors
inferredcites →https://doi.org/10.1207/s15327906mbr2704_2openalex-extracted
Remarks on Parallel Analysis
inferredcites →https://doi.org/10.1214/12-aos970openalex-extracted
Factor modeling for high-dimensional time series: Inference for the number of factors
inferredcites →https://doi.org/10.1214/15-sts539openalex-extracted
Bi-Cross-Validation for Factor Analysis
inferredcites →https://doi.org/10.3390/s18092892openalex-extracted
Feature Representation and Data Augmentation for Human Activity Classification Based on Wearable IMU Sensor Data Using a Deep LSTM Neural Network
inferredcites →https://doi.org/10.3982/ecta8968openalex-extracted
Eigenvalue Ratio Test for the Number of Factors
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