In SVMs (Support vector machines) Data points are log-transformed and normalized as in method A, where for N observations of a gene i, the log transform Xi of the expression level Ei and reference level Ri is? Options: A . &nbspXi = \(\frac{Log (E_i/R_i)}{\sqrt{\sum_{j=1,N} Log_{z-2} (E_j/R_j)}}\) B . &nbspXj = \(\frac{Log (E_j/R_i)}{\sqrt{\sum_{j=1,N} Log_z (E_j/R_j)}}\) C . &nbspXi = \(\frac{Log (E_i/R_i)}{\sqrt{\sum_{j=1,(N-1)} Log_z (E_j/R_j)}}\) D . &nbspXi = \(\frac{Log (E_i/R_i)}{\sqrt{\sum_{j=1,N} Log_z (E_j/R_j)}}\)

In SVMs (Support vector machines) Data points are log-transformed and normalized

Question

In SVMs (Support vector machines) Data points are log-transformed and normalized as in method A, where for N observations of a gene i, the log transform Xi of the expression level Ei and reference level Ri is?

Options:

A . Xi = \(\frac{Log (E_i/R_i)}{\sqrt{\sum_{j=1,N} Log_{z-2} (E_j/R_j)}}\)

B . Xj = \(\frac{Log (E_j/R_i)}{\sqrt{\sum_{j=1,N} Log_z (E_j/R_j)}}\)

C . Xi = \(\frac{Log (E_i/R_i)}{\sqrt{\sum_{j=1,(N-1)} Log_z (E_j/R_j)}}\)

D . Xi = \(\frac{Log (E_i/R_i)}{\sqrt{\sum_{j=1,N} Log_z (E_j/R_j)}}\)

Answer: Option A
Answer: (a).Xi = \(\frac{Log (E_i/R_i)}{\sqrt{\sum_{j=1,N} Log_{z-2} (E_j/R_j)}}\)

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