Tom: 41 Strona: 73

Autorzy:
Anna Bartkowiak
Adam Szustalewicz

Tytuł:
LARS regression in diagnosing mammograms: selection of variables for analysis

Język: Angielski

Słowa kluczowe:
fractal signatures
mammogram diagnostics
linear regression
reduction of predictors
forward search
least angle regression
lars
correct classification
cross-validation

Streszczenie:
Diagnosing cancer in a mammogram is a difficult task. Our aim is to explore the usefulness of so called fractal signatures for this purpose. A fractal signature is given by a vector of p real numbers characterizing the roughness of a mammogram considered as a texture file. Fractal signa-tures of length 48 are considered. Are all of them relevant to make the 2–group diagnosis: non–cancer or cancer? To answer this question, we used the Least–Angle Regression (LARS) which is believed more stable than the traditional forward search. By 5–fold cross–validation we found that only a small subset of variables is relevant for the diagnosis. The considerations are illustrated using data from the MIAS data base.

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