Principal Component Analysis (PCA)

This algorithm is a legacy one. The API has changed since its implementation. New versions and forks will need to be updated.

Algorithms have at least one input and one output. All algorithm endpoints are organized in groups. Groups are used by the platform to indicate which inputs and outputs are synchronized together. The first group is automatically synchronized with the channel defined by the block in which the algorithm is deployed.

Unnamed group

Endpoint Name Data Format Nature
image system/array_2d_uint8/1 Input
subspace tutorial/linear_machine/1 Output

Parameters allow users to change the configuration of an algorithm when scheduling an experiment

Name Description Type Default Range/Choices
number-of-components uint32 5

The code for this algorithm in Python
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This algorithm performs principal component analysis (PCA) [PCA] on a given dataset using the singular value decomposition (SVD) [SVD].

This implementation relies on the Bob library.

The input image is a training set of floating point vectors as a two-dimensional array of floats (64 bits), the number of rows corresponding to the number of training samples, and the number of columns to the dimensionality of the training samples.

The output subspace is a linear transformation as a collection of weights, biases, input subtraction and input division factors.

[SVD]http://en.wikipedia.org/wiki/Singular_value_decomposition
[PCA]http://en.wikipedia.org/wiki/Principal_component_analysis

Experiments

Updated Name Databases/Protocols Analyzers
anjos/tutorial/eigenface/1/atnt-eigenfaces-75-comp-bis atnt/3@idiap tutorial/postperf_iso/1
anjos/tutorial/eigenface/1/atnt-eigenfaces-172 atnt/3@idiap tutorial/postperf_iso/1
tutorial/tutorial/eigenface/1/atnt-eigenfaces-70-comp atnt/3@idiap tutorial/postperf_iso/1
tutorial/tutorial/eigenface/1/atnt-eigenfaces-50-comp atnt/3@idiap tutorial/postperf_iso/1
tutorial/tutorial/eigenface/1/atnt-eigenfaces-45-comp atnt/3@idiap tutorial/postperf_iso/1
tutorial/tutorial/eigenface/1/atnt-eigenfaces-7-comps atnt/3@idiap tutorial/postperf_iso/1
tutorial/tutorial/eigenface/1/atnt-eigenfaces-8-comps atnt/3@idiap tutorial/postperf_iso/1
tutorial/tutorial/eigenface/1/atnt-eigenfaces-9-comps atnt/3@idiap tutorial/postperf_iso/1
namratachede/tutorial/eigenface_with_preprocessing/1/namrataTest2 atnt/2@idiap tutorial/postperf_iso/1
omenemac/omenemac/gagatoolchainfork/1/MacsExperiment4 atnt/2@idiap tutorial/postperf_iso/1
chennu/tutorial/eigenface_with_preprocessing/1/test21 atnt/2@idiap tutorial/postperf_iso/1
soumik/tutorial/eigenface_with_preprocessing/1/Eigenface-22 atnt/2@idiap tutorial/postperf_iso/1
Vijay/tutorial/eigenface_with_preprocessing/1/Pparistest atnt/2@idiap tutorial/postperf_iso/1
mojtabaeslahi/cwhitela/cwhitela_eigenfaces_with_preprocessing/1/paristest atnt/2@idiap tutorial/postperf_iso/1
tutorial/tutorial/eigenface_with_preprocessing/1/paris-test atnt/2@idiap tutorial/postperf_iso/1
magedsoft/tutorial/eigenface_with_preprocessing/1/histogram_test_creteil atnt/2@idiap tutorial/postperf_iso/1
ilyaskhantmg/tutorial/eigenface/1/aint-15-comp atnt/2@idiap tutorial/postperf_iso/1
smarcel/tutorial/eigenface/1/eigenface-rr2 atnt/2@idiap tutorial/postperf_iso/1
cwhitela/cwhitela/cwhitela_eigenfaces_with_preprocessing/1/cwhitela_test atnt/2@idiap tutorial/postperf_iso/1
tutorial/tutorial/eigenface_with_preprocessing/1/atnt-eigenfaces-33-comp-histoeq atnt/2@idiap tutorial/postperf_iso/1
tutorial/tutorial/eigenface/1/atnt-eigenfaces-10-comp atnt/2@idiap tutorial/postperf_iso/1
tutorial/tutorial/eigenface/1/atnt-eigenfaces-9-comp atnt/2@idiap tutorial/postperf_iso/1
tutorial/tutorial/eigenface/1/atnt-eigenfaces-8-comp atnt/2@idiap tutorial/postperf_iso/1
tutorial/tutorial/eigenface/1/atnt-eigenfaces-7-comp atnt/2@idiap tutorial/postperf_iso/1
tutorial/tutorial/eigenface/1/atnt-eigenfaces-6-comp atnt/2@idiap tutorial/postperf_iso/1
tutorial/tutorial/eigenface/1/atnt-eigenfaces-5-comp atnt/2@idiap tutorial/postperf_iso/1
smarcel/tutorial/eigenface_with_preprocessing/1/eigenface-prepro-tutorial-pca15-ter atnt/1@idiap tutorial/postperf_iso/1
anjos/tutorial/eigenface_with_preprocessing/1/foorbar atnt/1@idiap tutorial/postperf_iso/1
pranayd/pranayd/pranay/1/pranay atnt/1@idiap tutorial/postperf_iso/1
pedro/tutorial/eigenface_with_preprocessing/1/eigenface-with-51-components atnt/1@idiap tutorial/postperf_iso/1
EderKapisch/EderKapisch/eigenface_preproc/1/eigenface-with-10-components atnt/1@idiap tutorial/postperf_iso/1
tutorial/tutorial/eigenface_with_preprocessing/1/eigenface-with-10-components-preproc atnt/1@idiap tutorial/postperf_iso/1
AntonioCandia/AntonioCandia/eigenface_preprop/1/eigenface-with-10-components atnt/1@idiap tutorial/postperf/1
tutorial/tutorial/eigenface_with_preprocessing/1/eigenface-with-preproc-15 atnt/1@idiap tutorial/postperf_iso/1
tutorial/tutorial/full_eigenface/1/mobioMale_eigenfaces_50comp mobio/1@male tutorial/eerhter_postperf_iso/1

This table shows the number of times this algorithm has been successfully run using the given environment. Note this does not provide sufficient information to evaluate if the algorithm will run when submitted to different conditions.

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