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How To Use Discriminate Function Analysis

10338
LDA approaches the problem by assuming that the conditional probability density functions

p
(

x

|

y
=
0
)

{\displaystyle p({\vec {x}}|y=0)}

and

p
(

address x

|

y
=
1
)

More Bonuses
{\displaystyle p({\vec {x}}|y=1)}

are both the normal distribution with mean and covariance parameters

(

0

,

0

)

{\displaystyle \left({\vec {\mu }}_{0},\Sigma _{0}\right)}

and

(
a knockout post

1

,

1

)

{\displaystyle \left({\vec {\mu }}_{1},\Sigma _{1}\right)}

, respectively. .