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two models have as similar a dimensionality as possible; that is, the threshold value is determined such that the two eigenspaces include the same amount of information on training samples. Compared with the Batch PCA, the proposed Chunk IPCA has slightly lower classi cation accuracy; however, the difference is not signi cant. This means that the proposed method ensures the quasi-optimality in the construction of eigenspace without keeping past training samples. The computation costs of the eigenspace update are estimated by measuring the CPU time using a MATLAB function. In Table 7.2b, the CPU time of Fixed Eigenspace corresponds to the time required to construct an initial feature space. As you can see in Table 7.2b, the computation costs of Chunk IPCA are signi cantly reduced against both Original IPCA and Batch PCA, especially for large data sets. However, for the Advertisement data set, Chunk IPCA has no advantage over Original IPCA, in which an intermediate eigenproblem is solved for every training sample. The main reason for this is that the computation costs of the eigen-axis selection could be expensive for largedimensional data because the large-scale matrix multiplication is needed many times for all eigen-axis candidates. However, this can be alleviated by introducing a more sophisticated search algorithm (e.g., binary search) in the eigen-axis selection. The experimental results here suggest that the proposed method possesses excellent scalability unless the number of attributes is too large.

Currently most psychologists are unable to provide invasive biological or medical interventions such as prescribing psychotropic medications or using ECT. However, psychologists have limited prescription privileges in several locations (i.e., New Mexico, Louisiana, Guam, the military), thereby allowing them to provide medications for their patients without physician supervision (Beutler, 2002; this issue will be discussed in more detail in 14). Although psychologists at present cannot prescribe medication and must work with physician colleagues in treating patients using these medications, in most states clinical psychologists need at least a basic understanding of commonly used psychotropic medications. They must be familiar with medications and their side effects and know when

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For the lower bound, let S be a random variable with a binomial distribution with parameters n and p. The most likely value of S is S = np . This can easily be veri ed from the fact that P (S = i + 1) n i p = P (S = i) i+11 p (11.47)

20 log(E2 / E0 ). 10 log(p2 / p0 )

Remember that the sign of this quantity is the hard decision of the estimated value, while its absolute value is the reliability of that decision. From this de nition, the following expressions are obtained: e L(bi ) = or P(bi = +1) = and P(bi = 1) = 1 1 + e L(bi ) (62) e L(bi ) 1 + e L(bi ) (61) P(bi = +1) P(bi = +1) = P(bi = 1) 1 P(bi = +1)

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