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inspect3d:documentation:knowledge_discovery:principal_component_analysis

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inspect3d pca graphs]]. this page includes: * visualizing the [[inspect3d:documentation:pages:pca_graphs#variance_explained|variance explained by each pc individually]]; * visualizing the [[inspect3d:documentation:pages:pca_graphs#loading_vector|variance explained by each pc at each point in the signal's cycle]]; * [[inspect3d:documentation:pages:pca_graphs#subject_scores|scatter-plotting workspace scores]] in pc-space; * showing the [[inspect3d:documentation:pages:pca_graphs#group_scores|distribution of scores by group]] for each pc; * visualizing the [[inspect3d:documentation:pages:pca_graphs#extreme_plot|mean and extreme values]] that result from reconstructing the underlying data with each pc; and * visualizing how the signals can be [[inspect3d:documentation:pages:pca_graphs#pc_reconstruction|reconstructed from the computed pcs]]. ===== tutorials ===== for a step-by-step example of how to use inspect3d to perform pca on your data, see the [[inspect3d:tutorials:perform_principal_component_analysis|pca tutorial]]. for a step-by-step example of how to use inspect3d to perform further statistical testing on pca results, see the [[inspect3d:tutorials:run_k-means|tutorial: run k-means]]. for a step-by-step example of processing and analyzing large data sets in inspect3d and using pca to distinguish between groups, see the [[inspect3d:tutorials:treadmill_walking_in_healthy_individuals|tutorial: treadmill walking in healthy individuals]] and the [[inspect3d:tutorials:analysis_of_baseball_hitters|tutorial: analysis of baseball hitters]].

inspect3d/documentation/knowledge_discovery/principal_component_analysis.1718801103.txt.gz · Last modified: 2024/06/19 12:45 by sgranger