教師あり学習

1. The Elements
of Statistical
Learning
#2 (2)

2. ! Y f(%)
k
2

3. Structured Regression Models

4. S
f
RSS $ = Σ'()
*
+' − $ -'
.
R
4

5. Classes of Restricted Estimators

6. 6
(1 1
)) 3 1
3

7. 2
7
RSS # 2
PRSS #; & = ()) # + &+(#)
+(#) #
2

8. 8
!"($%, $)
() (

9. 9
!" #$, # =
'
"
exp[−
-.-/
0
1"
]
#$
2 f(x$) f67(x$) 89
RSS f7, x$
RSS f7, x$ = Σ=>'
?
!" #$, #= @= − A7 #=
1
!" #$, #B @B − A7 #B
1
2

10. 10
:
!"($) = Σ()*
+
,(ℎ(($)
,(: : , ℎ( $

11. 11
!
"#(%) = Σ)*+
,
K./
(0), %)2)
0), 3)
"#(%) = Σ)*+
,
4)5(6)
7 % + 9))
5 % =
+
(+:;<=)

12. . 2
Model Selection and the Bias-Variance
Tradeoff

13. 13
2 0 2 0
2 0 0
! !

14. 14
()
)