SimSel - a new simulation feature selection method I

• In pharmaceutical research there are datasets describing the interactions between proteins and molecules. The datasets include a huge number of independent variables (features) and the response variable is typically the binding strength. Thus, one of the most challenging problems is to find the features that have a real influence on the binding strength.Here we present a feature selection method. The principle of the algorithm is to disturb each single feature by adding pseudo errors and to study the influence on the quality of the model fit.The main idea is that the change of unimportant features has no effect on the binding strength.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Farmakologi och toxikologi (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Pharmacology and Toxicology (hsv//eng)

NATURVETENSKAP  -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)

NATURAL SCIENCES  -- Mathematics -- Probability Theory and Statistics (hsv//eng)

Keyword

variable selection

model choice

regression

simulation method

pseudoerrors

SIMEX

residual sum of squares

Pharmaceutical pharmacology

Farmaceutisk farmakologi

Mathematical statistics

Matematisk statistik

Publication and Content Type

vet (subject category)

rap (subject category)