Classification of anabolic steroids

  Class Peak (W/m 2 )between 1 and 8 Angstroms   B  I < 10 -6   C  10 -6 < = I < 10 -5   M  10 -5 < = I < 10 -4   X  I > = 10 -4

Most algorithms describe an individual instance whose category is to be predicted using a feature vector of individual, measurable properties of the instance. Each property is termed a feature , also known in statistics as an explanatory variable (or independent variable , although features may or may not be statistically independent ). Features may variously be binary (. "male" or "female"); categorical (. "A", "B", "AB" or "O", for blood type ); ordinal (. "large", "medium" or "small"); integer-valued (. the number of occurrences of a particular word in an email); or real-valued (. a measurement of blood pressure). If the instance is an image, the feature values might correspond to the pixels of an image; if the instance is a piece of text, the feature values might be occurrence frequencies of different words. Some algorithms work only in terms of discrete data and require that real-valued or integer-valued data be discretized into groups (. less than 5, between 5 and 10, or greater than 10)

Classification of anabolic steroids

classification of anabolic steroids

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