Data Mining: Practical Machine Learning Tools and Techniques, Second Edition

64.6

(24/19.2%)

CHMIN

≤ 7.5 > 7.5

MMAX

≤ 8.5 (8.5,28]

MMAX

> 28

19.3

(28/8.7%)

≤ 2500

29.8

(37/8.18%)

(2500,

4250]

CACH

> 4250

MYCT

≤ 0.5

59.3

(24/16.9%)

(0.5,8.5]

≤ 550

37.3

(19/11.3%)

18.3

(7/3.83%)

> 550

75.7

(10/24.6%)

≤ 10000

133

(16/28.8%)

> 10000

157

(21/73.7%)

≤ 28000 > 28000

MMIN

≤ 58

783

(5/359%)

> 58

281

(11/56%)

≤ 12000

492

(7/53.9%)

> 12000

CACH MMAX

CHMAX

(b)

CHMIN

≤ 7.5 > 7.5

≤ 8.5

LM4

(50/22.1%)

> 8.5

LM1

(65/7.32%)

≤ 4250 > 4250

≤ 0.5

LM2

(26/6.37%)

LM3

(24/14.5%)

(0.5,8.5]

LM5

(21/45.5%)

≤ 28000

LM6

(23/63.5%)

> 28000

MMAX

CACH

MMAX

CACH

(c)

LM1 PRP=8.29+0.004 MMAX+2.77 CHMIN

LM2 PRP=20.3+0.004 MMIN-3.99 CHMIN

+0.946 CHMAX

LM3 PRP=38.1+0.012 MMIN

LM4 PRP=19.5+0.002 MMAX+0.698 CACH

+0.969 CHMAX

LM5 PRP=285-1.46 MYCT+1.02 CACH

-9.39 CHMIN

LM6 PRP=-65.8+0.03 MMIN-2.94 CHMIN

+4.98 CHMAX

PRP =
-56.1
+0.049 MYCT
+0.015 MMIN
+0.006 MMAX
+0.630 CACH
-0.270 CHMIN
+1.46 CHMAX
(a)

Figure 3.7Models for the CPU performance data: (a) linear regression, (b) regression
tree, and (c) model tree.