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4 SPARSE BAYESIAN LEARNING

The prior of each component wi of w is now set separately ...............

4 SPARSE BAYESIAN LEARNING The prior of each component wi of w is now set separately-example-1
User Mariy
by
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1 Answer

4 votes

Answer:

Answer:

WF=34

Explanation:

Point I lies between points W and F.

It means point WI + IF = WF

SO WI + IF = WF

=

WF = 15x – 21

WI= 7x-3

IF= 2x+4

WI + IF = WF

7x-3 +2x+4= 15X-21

7x+2x-15x= -21-4+3

-6x = -22

X= -22/6

X= 11/3

So WF = 15x – 21

WI= 7x-3

IF= 2x+4

WI + IF = WF

=

7X-3 +2x+4= 15x-21

7x+2x-15x= -21-4+3

-6x = -22

X= -22/6

X= 11/3

So WF = 15x – 21

WF= 15(11/3) -21

WF= 55-21

WF=34

User Parkar
by
3.5k points