Pattern Recognition and Machine Learning

(Jeff_L) #1


E[x]. If the distribution ofxis conditioned on another variablez, then the corre-
sponding conditional expectation will be writtenEx[f(x)|z]. Similarly, the variance
is denotedvar[f(x)], and for vector variables the covariance is writtencov[x,y].We
shall also usecov[x]as a shorthand notation forcov[x,x]. The concepts of expecta-
tions and covariances are introduced in Section 1.2.2.
If we haveNvaluesx 1 ,...,xNof aD-dimensional vectorx=(x 1 ,...,xD)T,
we can combine the observations into a data matrixXin which thenthrow ofX
corresponds to the row vectorxTn. Thus then, ielement ofXcorresponds to the
ithelement of thenthobservationxn. For the case of one-dimensional variables we
shall denote such a matrix byx, which is a column vector whosenthelement isxn.
Note thatx(which has dimensionalityN) uses a different typeface to distinguish it
fromx(which has dimensionalityD).
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