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CLUSTER >> CLUSTER > PCAScatterPlot

PCAScatterPlot

performs a 2D principal component analysis (PCA) and visualizes it.

Calling Sequence

PCAScatterPlot(Samples, Color, Marker)

Parameters

Samples:

matrix that includes sample vectors as rows

Color:

string that specifies marker color, can be 'r' (red), 'y' (yellow), 'g' (green), 'c' (cyan), 'b' (blue), 'm' (magenta) or 'k' (black)

Marker:

string that specifies the character used as marker, can be '.' (point), 'o' (circle), '+' (plus), '*' (asterisk) or 'x' (cross)

Description

This function applies a 2D principal component analysis (PCA) to the rows of Samples. All samples are projected to the plane spanned by the 1st and 2nd principal components.

Examples

global CLUSTER_PATH;
Source = read_csv(CLUSTER_PATH + 'demos\IrisData.csv', ascii(9));
Samples = strtod(Source(:, 1 : 4));
PCAScatterPlot(Samples, 'r', '.');

See also

Authors

Bibliography

Harald Galda, 'Development of a segmentation method for dermoscopic images based on color clustering', Kobe University, August 2003


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