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## Why Not Store Everything in Main Memory? Why use disks?

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### GRADIENT(V) = 2A o d 2a11 2a12 ... 2a1n 2a21 2a22 ... 2a2n: ' 2an1 ... 2ann d1: di: dn Compute Median(DPPd(X)? Want to use only pTree processing. Want a formula in ... – PowerPoint PPT presentation

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Title: Why Not Store Everything in Main Memory? Why use disks?

1
FAUST CLUSTERING
Use DPPd(x), but which unit vector, d, provides
the best gap(s)?
1. DPPd exhaustively searches a grid of d's for
the best gap provider.
2. Use some heuristic to choose a good d?
GV Gradient-optimized Variance MM Use the d
that maximizes MedianF(X)-Mean(F(X)).
We have Avg as a function of d.
Median? (Can you do it?) HMM Use a heuristic
for MedianF(X) F(VectorOfMedians)VOMod MVM
Use DMEAN(X)?VOM(X), dD/D
Maximize variance - is it wise?
0 0 0 0 0
0 0 0 1 0 5
0 0 0 0 0
2 0 5 2 0 0 0
0 3 0 5 2 3
0 0 0 4 0
5 4 3 6 0 0 median
5 0 5 4 3 6 9
0 6 0 5 6 6
6 9 10 7 0
5 6 6 6 9 10
8 0 5 8 6 9 9
10 9 0 5 8
9 9 9 10 10 10
10 10 10 10 10 10 std
3.16 2.87 2.13 3.20 3.35 3.82 4.57
4.98 variance 10.0 8.3 4.5 10.2
11.2 14.6 20.9 24.8 Avg 5.00
0.91 5.00 4.55 4.18 4.73 5.00
4.55 consecutive 1 0 5 0
0 0 0 0 differences 1 0
0 2 0 0 0 0
1 0 0 0 3 0 0
0 1 0 0 2
0 6 0 0 1 0
0 0 0 0 9 0
1 0 0 2 3 0
0 10 1 0 0 0
0 0 0 0 1
0 0 2 0 3 0 0
1 0 0 0 3 0
0 0 1 10 5 2
1 1 1 0 avgCD 1.00
1.00 1.00 1.00 1.00 1.00 1.00
1.00 maxCD 1.00 10.00 5.00 2.00
3.00 6.00 9.00 10.00 mean-VOM 0.00
0.91 0.00 0.55 1.18 1.27 4.00 4.55
2
What have we learned? What is the DPPd FAUST
CLUSTER algorithm?
DMedian?Mean, d1D/D is a good start. But
first, Variance-Gradient hill-climb it. (Median
means Vector of Medians).
For X2SubCluster2 use a d2 which is
perpendicular to d1? In high dimensions, there
are many perpendicular directions. GV hill-climb
d2D2/D2 (D2MedianX2-MeanX2) constrained to be
? to d1, i.e., constrained to d2od10 (in
addition to d2od21. We may not want to constrain
this second hill-climb to unit vectors
perpendicular to d1. It might be the case that
the gap gets wider using a d2 which is not
perpendicular to d1?
GMP Gradient hill-climb (wrt d) VarianceDPPd
starting at d2D2/D2 where d2Unitized(
Vomx-xod1x?X2 - Meanx-xod1x?X2 )
Variance-Gradient hill-climbed subject only to
dod1
(We shouldn't constrain the 2nd hill-climb to
d1od20 and subsequent hill-climbs to dkodh0,
h2...k-1. (gap could be larger). So the 2nd
round starts at d2Unitized( Vomx-xod1x?X2 -
Meanx-xod1x?X2 ) and hill-climbs subject only
to dod1)
GCCP Gradient hill-climb (wrt d) VarianceDPPd
starting at d2D2/D2 where D2CCi(X2)-CCj(X2),
and hill-climbs subject to dod1, where the CCs
are two of the Circumscribing rectangle's Corners
(the CCs may be a faster calculations than Mean
and Vom). Taking all edges and diagonals of
CCR(X) (the Coordinate-wise Circumscribing
Rectangle of X) provides a grid of unit vectors.
It is an equi-spaced grid iff we use a CCC(X)
(Coordinate-wise Circumscribing Cube of X). Note
that there may be many CCC(X)s. A canonical one
is the one that is furthest from the origin (take
the longest side first. Extend each other side
the same distance from the origin side of that
edge. A good choice may be to always take the
longest side of CR(X) as D, DLSCR(X). Should
outliers on the (n-1)-dim-faces at the ends of
LSCR(X) be removed first? So remove all
LSCR(X)-endface outliers until after removal the
same side is still the LSCR(X). Then use that
LSCR(X) as D.
3
MVM
C11 F-MN gp?2 0 1 1 1 1 1 2 3 1 3
3 2 5 2 1 6 1 2 8 2 2 10 2
1 11 1 1 12 4 1 13 1 2 15 2
WINE
GV
ACCURACY WINE GV 62.7 MVM 66.7 GM
81.3
GM
.11 .19 .96 .19 209 -.02 .41 .91 0
232 C1(F-MN) gp?3 0 1 1 1 6 1 2 5
1 3 2 1 4 4 1 5 8 1 6 8 1 7
4 1 8 3 1 9 7 1 10 1 1 11 4
1 12 6 1 13 4 1 14 2 1 15 3 1 16
3 1 17 2 1 18 2 1 19 3 1 20 4
1 21 6 1 22 4 1 23 1 1 24 2 1 25
4 1 26 1 1 27 1 2 29 2 1 30 2
2 32 1 3 35 1 1 36 1 1 37 1 1 38
1 1 39 4 1 40 2 2 42 2 2 44 1
1 45 2 2 47 4 1 48 2 1 49 1 1 50
1 3 53 1 1 54 2 1 55 2
0.12)
1L 0H
F-MN Ct gp?8 0 1 12 12 1 3 15 2 13
28 1 2 30 1 2 32 2 2 34 1 1
35 2 3 38 1 8 46 1 1 47 3 10
57 1 1 58 1 1 59 1 1 60 1 2
62 1 2 64 1 1 65 1 1 66 1 1
67 4 1 68 2 1 69 1 1 70 1 2
72 3 1 73 1 1 74 3 1 75 2 1
76 1 1 77 1 2 79 1 3 82 1 1
83 1 1 84 2 1 85 1 1 86 1 2
88 2 1 89 4 1 90 2 1 91 1 1
92 6 1 93 3 1 94 5 1 95 4 2
97 5 1 98 2 1 99 1 1 100 4
1 101 7 1 102 4 1 103 2 1 104 3
1 105 6 1 106 3 1 107 8 1 108 10
1 109 2 1 110 4 1 111 5 1 112 2
1 113 4 1 114 1
.07 .15 .98 .12 588 -.01 .26 .97 .00 608 (F-MN)
gp?8 0 1 1 1 4 1 2 4 1 3 5
1 4 4 1 5 6 1 6 8 1 7 6
1 8 4 1 9 5 1 10 2 1 11 3
1 12 7 1 13 4 1 14 3 1 15 2
1 16 2 1 17 3 1 18 4 1 19 3
1 20 4 1 21 1 1 22 7 1 23 2
1 24 4 1 25 1 1 26 1 1 27 1
1 28 1 1 29 1 1 30 1 1 31 1
1 32 1 3 35 1 2 37 3 1 38 1
1 39 1 1 40 3 1 41 3 3 44 2
1 45 2 1 46 4 1 47 2 2 49 1
2 51 1 1 52 1 3 55 1 1 56 1
1 57 1 9 66 2 1 67 2 8 75 1
4 79 2 1 80 1 2 82 2 1 83 1
2 85 1 13 98 1 2 100 1 3 103 1
11 114 1
-.05 -.31 -.95 -.01 605 .01 -.27 -.96 -.0
608 XF-M gp?3 0 1 11 11 1 4 15 1 1 16
1 13 29 1 1 30 1 2 32 2 2 34 1
1 35 2 4 39 1 8 47 2 1 48 2 9 57
1 1 58 1 1 59 1 2 61 1 2 63 1
2 65 1 1 66 1 1 67 1 1 68 5 1 69
2 1 70 1 3 73 3 1 74 3 1 75 1
1 76 2 1 77 2 2 79 1 3 82 1 1 83
1 1 84 1 1 85 1 1 86 1 1 87 1
1 88 1 1 89 1 1 90 4 1 91 2 1 92
7 1 93 1 1 94 5 1 95 4 1 96 2
1 97 3 1 98 2 1 99 2 1 100 3 1 101
4 1 102 7 1 103 3 1 104 2 1 105 6
1 106 3 1 107 5 1 108 9 1 109 6 1 110
4 1 111 5 1 112 4 1 113 4 1 114 1
_4L 2H
___ _ 12,28) 1L 2H
_2L 1H
2L 0H C1
-.11 -.02 -.86 .5 43 -.05 -.4 -.92 .01 68 C7F-M3
g?3 0 1 3 3 1 2 5 1 4 9 2
6 15 1 3 18 1 2 20 1 1 21 1 1 22
3 3 25 2 3 28 1 2 30 3 1 31 2
1 32 1 1 33 1 1 34 2 1 35 1 1 36
3 3 39 2 1 40 1 1 41 2 3 44 1
2 46 3 2 48 1 2 50 2 2 52 1 1 53
1 1 54 1 1 55 1 1 56 2 1 57 1
1 58 2 1 59 2 1 60 2 1 61 1 1 62
1 1 63 2 2 65 1 1 66 1 1 67 1
1 68 1 1 69 3 1 70 1 1 71 1 1 72
1 1 73 1 1 74 2 1 75 2 1 76 1
1 77 3 1 78 4 1 79 3 1 80 4 1 81
1 1 82 1 1 83 1 2 85 2 1 86 2
2 88 3 1 89 2 2 91 2 2 93 4 3 96
1
_0L 2H
_0L 2H C2
3L 5H
-.08 .59 -.8 -.07 80 .08 .83 -.56 -.01 95
C5 g?3 0 1 4 4 1 8 12 1 3 15 1
2 17 1 2 19 1 4 23 1 1 24 1 2 26
1 1 27 1 2 29 3 2 31 1 1 32 1
1 33 1
___ _ 28,46) 2L 6H
1L 1H
___ _ 46,57) 2L 2H
.05 .59 -.293 .75 18 -.1 .9 -.3 .1 34 C68
?16 0 1 4 4 2 16 20 1 11 31 1
37 68 1 15 83 1 15 98 1 8 106 1
11 117 1 1 118 2
_2L 4H C71
C121 max thin 0 1 1 1 6 1 2 5 1
3 3 1 4 3 1 5 8 1 6 8 1 7 4
1 8 7 1 9 3 1 10 1 1 11 5
1 12 6 1 13 3 1 14 2 1 15 3 1 16
3 1 17 4
_2L 5H C3
_0L 1H C4
_3L 0H
C1 F-M Ct g?3 0 1 1 1 2 1 2 2
3 5 1 1 6 1 1 7 4 1 8 2
2 10 2 1 11 1 2 13 2 1 14 1
1 15 1 1 16 5 2 18 1 2 20 2
3 23 1 1 24 1 1 25 1 1 26 2
2 28 1 1 29 1 1 30 5 1 31 2
1 32 1 1 33 4 1 34 5 1 35 4
1 36 4 1 37 2 1 38 3 1 39 3
1 40 2 1 41 4 1 42 3 1 43 5
1 44 3 1 45 4 1 46 5 1 47 4
1 48 3 1 49 11 1 50 5 1 51 3
1 52 5 1 53 4 1 54 4 1 55 1
_1L 2H
___ 4L 2H
_0L 1H C4
___ 0L 2H
_1L 2H
_2L
3L 2H
23L 25H 6L 21H
_1L 6H
5L 5H
_2L 12H
_9L 7H C5
.19 .8 -.54 .18 7 -.21 .7 -.7 -.09 9
C763F-M8 g?8 0 2 16 16 1 13 29 1
12 41 2 4 45 1 7 52 1 4 56 1 7 63
1 8 71 2
_1L 4H
.01 -.27 -.96 -.01 23 -.04 -.43 -.9 .03
24 C764 g?3 0 1 31 31 1 3 34 1 1 35
2 2 37 1 2 39 2 2 41 1 2 43 1
1 44 1 2 46 3 3 49 1 1 50 1 1 51
2 1 52 1 1 53 2 2 55 2 2 57 2
3 60 1 2 62 2 1 63 1 2 65 3 1 66
2 3 69 1 1 70 1 1 71 2 2 73 2
1 74 1 1 75 2 1 76 3 1 77 2 1 78
2 1 79 3 1 80 3 2 82 1 2 84 1
2 86 2 1 87 1 1 88 1 2 90 2 1 91
2 3 94 2 2 96 2 1 97 2
C11 10L 13H C12
0L 2H
___ _1L 0H
___ _0L 1H
_2L 0H
0.35) C11
38L 68H
C12 F-M gp?2 0 1 1 1 8 1 2 3 1 3
2 1 4 4 1 5 11 1 6 8 1 7 2
1 8 6 1 9 4 1 10 3 1 11 4 1 12
4 1 13 5 1 14 3 1 15 3 1 16 4
2 18 2 1 19 5 1 20 6 1 21 4 1 22
1 1 23 2 1 24 3 1 25 3 3 28 2
1 29 2 2 31 1
4L 8H C6
_2L 4H
4L8H C763
_0L 2H
-.21 .34 -.91 .9 8 C766 16 g?4 0 1 30 30 1
2 32 1 7 39 1 1 40 1 1 41 1
1 42 1 4 46 1 2 48 1 2 50 2 5 55
1 3 58 1 7 65 1 2 67 1 5 72 1
3 75 2 2 77 1 1 78 4 2 80 1 3 83
1 1 84 2 4 88 1 1 89 1 11 100 1
4 104 1 11 115 1
_0L 1H
35,53) C12
10L 13H
___ _ 2L 9H
_2L 0H
___ 53,56) 3L 2H
_3L 1H
29L 46H
___ _ 1L 8H
51L 83H
0.66) C1
_1L 3H
___ _ 66,75) 2L 2H
_2L 0H
_2L 0H
7L 19H
2L 2H
___ _ 75,98) 2L 6H
0L 1H
___ 57,115) 51L 83H C1
_4L 8H
___ _ 98,115) 2L 2H
17L 15H C766
38L 68H C7
_2L 0H
_0L 2H
___ 28L 44H C76 1L
_1L 0H
___ _ 3L 3H
4
SEEDS
GV
MVM
ACCURACY SEEDS WINE GV 94 62.7 MVM
93.3 66.7 GM 96 81.3
219 31 14 29 akk d1 d2 d3 d4 V(d .98 .14
.06 .13 9 .98 .14 .06 .13 9 10(F-MN) gp?6 0
2 1 1 10 1 2 5 1 3 1 6 9 3 1
10 10 1 11 10 1 12 2 6 18 2 1 19
3 1 20 7 1 21 2 1 22 1 1 23 3 6
29 6 1 30 4 1 31 7 1 32 1 6 38
1 1 39 2 1 40 6 1 41 5 1 42 1 7
49 3 1 50 1 2 52 7 1 53 2 7 60
1 2 62 4 1 63 3 8 71 5 1 72 2 2
74 1 6 80 5 1 81 8 1 82 5 1 83
3 9 92 2 10 102 1 1 103 2 1 104 1
10(F-MN)gp?6 0 2 1 1 10 1 2 5 1 3
1 6 9 3 1 10 10 1 11 10 1 12 2
6 18 2 1 19 3 1 20 7 1 21 2 1 22
1 1 23 3 6 29 6 1 30 4 1 31 7
1 32 1 6 38 1 1 39 2 1 40 6 1 41
5 1 42 1 7 49 3 1 50 1 2 52 7
1 53 2 7 60 1 2 62 4 1 63 3 8 71
5 1 72 2 2 74 1 6 80 5 1 81 8
1 82 5 1 83 3 9 92 2 10 102 1 1 103
2 1 104 1
___ ___ 0,9) 0k 0r 18c C1
___ ___ 0,9) 0k 0r 18c C1
___ ___ 9,18) 1k 0r 24c C2
GM
___ ___ 9,18) 1k 0r 24c C2
.794 -.403 -.304 .337 6 0.957 .156 -.205 .132
9 10(F-MN) gp?3 0 1 2 2 1 2 4 4
2 6 3 2 8 7 2 10 2 2 12 1
2 14 1 2 16 10 2 18 10 1 19 2
3 22 2 1 23 2 1 24 1 1 25 1
2 27 4 2 29 4 2 31 4 2 33 2
5 38 3 1 39 3 2 41 7 2 43 2
2 45 2 1 46 1 2 48 1 1 49 1
1 50 4 2 52 5 1 53 1 1 54 3
3 57 2 2 59 3 2 61 3 1 62 1
2 64 3 2 66 3 3 69 5 7 76 1
2 78 2 2 80 2 2 82 4 2 84 1
2 86 1 2 88 4 1 89 1 1 90 8
2 92 5 11 103 2 1 104 1 1 105 1
1 106 1 2 108 1
___ ___ 18,29) 10k 0r 8c C3
___ ___ 18,29) 10k 0r 8c C3
___ ___ 29,38) 18k 0r 0c C4
___ ___ 29,38) 18k 0r 0c C4
___ ___ 38,49) 13k 2r 0c C5
-.577 .577 .577 .000 1 .119 .112 .986 .000
3 C2 10(F-MN) gp?10 0 1 10 10 2 1 11 3
10 21 3 10 31 5 10 41 1 10 51 1
11 62 1 1 63 1
___ ___ 0,22) 0k 0r 42c C1
___ ___ 38,49) 13k 2r 0c C5
___ ___ 49,60) 7k 6r 0c C6
___ ___ 0,31) 9k 0r 0c C21
___ ___ 49,60) 7k 6r 0c C6
___ ___ 60,71) 1k 7r 0c C7
___ ___ 31,41) 1k 0r 4c C22
___ ___ 60,71) 1k 7r 0c C7
___ ___ 71,80) 0k 8r 0c C8
___ ___ 22,33) 10k 0r 8c C2
___ ___ 41,64) 0k 0r 4c C23
___ ___ 71,80) 0k 8r 0c C8
___ ___ 80,92) 0k 21r 0c C9
___ ___ 92,102) 0k 2r 0c Ca
___ ___ 80,92) 0k 21r 0c C9
___ ___ 92,102) 0k 2r 0c Ca
___ ___ 102,105) 0k 4r 0c Cb
C3 200(F-MN)gp?12 0 2 12 12 3 12 24 3
12 36 5 12 48 1 12 60 1 12 72 1
40 112 2
___ ___ 102,105) 0k 4r 0c Cb
___ ___ 33,57) 33k 2r 0c C3
C3 .97 .15 .09 .14 0 0 .07 1 0 4
10F-M g?9 0 2 10 10 3 10 20 3 10 30 4
1 31 1 9 40 1 10 50 1 11 61 1 9 70 2
___ ___ 0,35) 8k 0r 0c
___ ___ 0,10) 2k 0r 0c
___ ___ 35,48) 2k 0r 3c
___ ___ 10,20) 2k 0r 1c
-.832 -.282 .134 -.458 0 -.44 .00 -.87
-.22 2 C4 10(F-MN) gp?21 0 3 11 11 2
20 31 3 21 52 3 27 79 1 20 99 3
___ ___ 20,30) 2k 0r 1c
___ ___ 48,72) 0k 0r 2c
___ ___ 57,69) 6k 9r 0c C4
___ ___ 69,76) 1k 4r 0c C6
___ ___ 30,40) 4k 0r 1c
___ ___ 72,113) 0k 0r 3c
___ ___ 40,50) 0k 0r 1c
___ ___ 50,61) 0k 0r 1c
___ ___ 61,70) 0k 0r 1c
___ ___ 0,52) 1k 7r C41
___ ___ 70,71) 0k 0r 2c
___ ___ 52,79) 1k 2r C42
C6 200(F-MN)gp?12 0 3 12 12 1 38 50 3
10 60 1 2 62 3 12 74 2
___ ___ 79100) 4k 0r C43
___ ___ 0,50) 4k 0r 0c
___ ___ 50,60) 1k 0r 2c
___ ___ 76,103) 0k 26r 0c C7
___ ___ 0,22) 4k 0r 0c
___ ___ 60,74) 1k 0r 3c
___ ___ 74,75) 1k 0r 1c
___ ___ 103,109) 0k 6r 0c C8
___ ___ 22,49) 3k 6r 0c
5
MVM
.81 .28 -.28 .42 13... .53 .23 .73 .37
39 C12 4F-M g?3 0 2 4 4 1 4 8 2
2 10 1 2 12 1 2 14 1 3 17 1 1 18
1 2 20 1 1 21 1 1 22 1 2 24 3
1 25 1 2 27 1 1 28 1 2 30 1 4 34
1 2 36 2 2 38 1 3 41 2 3 44 1
2 46 2 2 48 1 2 50 1 2 52 2 2 54
1 1 55 1 1 56 1 1 57 1 1 58 3
1 59 1 1 60 2 2 62 1 1 63 4 2 65
1 1 66 1 1 67 1 1 68 1 1 69 3
3 72 1 2 74 1 2 76 1 2 78 1 1 79
1 3 82 1 2 84 1 1 85 1 4 89 1
1 90 1 2 92 1 1 93 1
C2 3762 808 2260 266 d1 d2 d3 d4 .84 .18 .51
.06 64 .57 .22 .71 .34 82 .51 .22 .74 .38
83 (F-MN)3 Ct gp?3 0 1 2 2 1 1
3 1 2 5 1 15 20 2 3 23 1 3 26 2
2 28 1 1 29 1 2 31 1 2 33 2 2
35 2 2 37 1 1 38 3 1 39 1 1 40 1
1 41 1 1 42 1 4 46 1 1 47 2 2
49 1 1 50 1 1 51 1 2 53 1 1 54 2
2 56 1 2 58 1 1 59 2 2 61 2 1
62 2 1 63 3 1 64 1 1 65 2 2 67 3
1 68 2 1 69 1 1 70 2 1 71 2 1
72 2 2 74 1 1 75 1 2 77 1 1 78 1
1 79 1 2 81 1 2 83 1 1 84 1 3
87 2 1 88 1 1 89 1 1 90 2 1 91 1
1 92 2 3 95 1 1 96 2 1 97 1 2
99 1 2 101 2 2 103 1 3 106 3 3 109 1
1 110 1 1 111 1
IRIS GM
GV
ACCURACY IRIS SEEDS WINE GV 82.7 94
62.7 MVM 94 93.3 66.7 GM 94.7
96 81.3
C23 F-M3 g?3 3847 818 2284 257 .96 .22 .06 -.14
15 0 1 6 6 1 2 8 1 4 12 1 3
15 1 1 16 1 2 18 2 8 26 1 2 28 1
1 29 1 1 30 1 2 32 1 1 33 1 3
36 1 3 39 2 1 40 1 1 41 2 1 42 2
2 44 2 2 46 1 1 47 2 5 52 1 1
53 1 3 56 1 1 57 1 3 60 1 1 61 1
1 62 1 2 64 1 6 70 2 5 75 1 2
77 2 3 80 1 9 89 1 8 97 1
F-MN gp?8 0 2 3 3 5 1 4 5 1 5
14 1 6 11 1 7 6 1 8 1 1 9 5
1 10 1 5 15 1 8 23 1 2 25 2 2 27
1 2 29 1 1.. 68 1
.88 .09 -.98 -.18 168 -.29 .13 -.88 -.36
417 -.36 .09 -.86 -.36 420 F-MN Ct gp?5 0
1 3 3 2 1 4 1 2 6 1 1 7 1
2 9 2 1 10 1 2 12 3 1 13 1 1 14
3 1 15 4 1 16 2 1 17 3 1 18 1
1 19 6 1 20 3 1 21 1 1 22 2 1 23
2 1 24 6 1 25 7 1 26 2 1 27 3
1 28 2 1 29 6 1 30 3 1 31 2 1 32
3 1 33 3 1 34 3 1 35 3 1 36 5
1 37 1 1 38 2 1 39 1 1 40 2 1 41
1 2 43 1 2 45 1 1 46 1 1 47 1
5 52 1 8 60 2 1 61 3 1 62 4 1 63
3 1 64 13 1 65 12 1 66 4 1 67 5
1 68 2 2 70 2
.90 .24 .37 .04 180 .41 -.04 .84 .35 418 .36
-.08 .86 .36 420 F-MN Ct gp?3 0 2 2 2 2
1 3 2 1 4 5 1 5 7 1 6 16 1 7
6 1 8 4 1 9 4 1 10 2 8 18 1
5 23 1 2 25 2 2 27 1 2 29 1 1 30
1 1 31 1 1 32 2 1 33 1 1 34 3
1 35 5 1 36 4 1 37 3 1 38 1 1 39
4 1 40 3 1 41 3 1 42 4 1 43 4
1 44 2 1 45 5 1 46 7 1 47 3 1 48
2 1 49 1 1 50 3 1 51 4 1 52 3
1 53 2 1 54 3 1 55 3 1 56 3 1 57
1 1 58 4 3 61 2 1 62 1 1 63 1
2 65 1 1 66 1 1 67 2 3 70 1
___ 1e 0i
-.36 .09 -.86 -.36 105 -.54 -0.17 -.76
-.33 118 C1 2(F-M g?3 0 2 4 4 1 1 5
1 1 6 1 5 11 1 2 13 1 3 16 1
2 18 1 3 21 1 1 22 1 1 23 1 2 25
2 1 26 2 2 28 2 1 29 1 2 31 3
1 32 1 2 34 1 1 35 2 1 36 2 1 37
4 3 40 2 1 41 1 2 43 3 2 45 1
2 47 4 1 48 1 1 49 2 1 50 4 1 51
3 2 53 5 1 54 2 1 55 2 1 56 1
1 57 3 2 59 3 2 61 2 2 63 1 1 64
1 1 65 2 2 67 1 1 68 1 1 69 2
1 70 2 1 71 3 1 72 1 1 73 2 2 75
1 1 76 1 1 77 1 1 78 1 1 79 1
1 80 1 2 82 2 10 92 1 2 94 2 2 96
1
__2e 5i
50s 1i C1 C2
___ 4e 1i C21
___ 19e 1i
C22 4(F-?) g?4 0 1 6 6 1 4 10 1
2 12 1 4 ... 33 2 1 34 1 4 38
1 1 39 1 3 ... 79 1 2 81 1 5
86 1 2 88 2 2 90 1 1 91 1 1
92 2 2 94 1 1 95 1 2 97 1 1
98 1 3 101 2 1 102 2 4 106 1
1 107 1 2 109 1 1 110 2 1 111 2
6 117 1 1 118 1 1 119 1 1 120 1
___50s 1i C1
___ 6e 0i
___ 18e

C221 29e 14i ___
___
___ 19e 1i C22
___28i C11
___ 16e 11i
18e 11i C123
___ 6e
___ 2e
___ 3e 2i
C221 8F-? g?5 0 1 7 7 1 4 11 1
5 16 1 1 17 1 3 20 1 1 21 1
2 23 1 1 24 1 5 29 1 3 32 2
2 34 1 1 35 1 4 39 3 5 44 1
3 47 2 3 50 1 3 53 1 4 57 1
3 60 1 3 63 1 1 64 2 5 69 2
1 70 1 3 73 1 1 74 1 1 75 1
4 79 1 1 80 2 2 82 2 1 83 1
1 84 1 2 86 1 4 90 1 5 95 1
___1e

___ 0e 3i
___ 2e

___ 26i

___ 0e 4i
C221 8F-?)g?5 0 1 7 7 1 4 11 1
5 16 1 1 17 1 3 20 1 1 21 1
2 23 1 1 24 1 5 29 1 3 32 2
2 34 1 1 35 1 4 39 3 5 44 1
3 47 2 3 50 1 3 53 1 4 57 1
3 60 1 3 63 1 1 64 2 5 69 2
1 70 1 3 73 1 1 74 1 1 75 1
4 79 1 1 80 2 2 82 2 1 83 1
1 84 1 2 86 1 4 90 1 5 95 1
___50e 49i C1
___ 3e .

__ 4e 1i

-.034 .37 -.31 .87 4 C123 12F-M g?4 0 1
6 6 1 10 16 1 2 18 1 3 21 1 1 22
1 1 23 1 6 29 1 3 32 1 3 35 1
5 40 2 5 45 1 4 49 1 1 50 2 4 54
1 2 56 1 5 61 2 1 62 1 2 64 1
1 65 1 2 67 1 3 70 1 1 71 1 12 83
1 1 84 1 1 85 1
__ 1i .
___ 50e 40i C2 9i C3
___ 1e .
_46e 21i C12
___9e

___ 5e 1i

___ 4e C13
___ 27e 16i C23
___9e .

___ 50s 1i C2
___ 9e 1i .
MVM C2 2(F-?)g?4 0 1 4 4 1 1 5 1
4 9 1 3 ... 69 1 4 73 1 1 74 1
2 76 2 4 80 1 4 84 1 2 86 2 5 91
1
__9e 2i

___ 9i C24
_ 4e .
__9e 2i

___ 3e

__ 0e 2i .
47e 40i C22

___ 8i
___ 3i
___ 2e 6i .
___ 5e 10i

___ _3i
___ 1i

___ 0e 11i

___ 2e 1i
___ 5e 11i

6
CONCRETE
GM
MVM C11 F-?/4 g?4 0 4 2 2 1 2 4 4
2 6 25 2 8 2 1 9 7 1 10 4 1 11
9 2 13 3 1 14 6 1 15 4 1 16 1
3 19 5 4 23 2 3 26 5 1 27 4 1 28
9 1 29 5 2 31 6 1 32 5 3 35 6
5 40 2
ACCURACY CONCRETE IRIS SEEDS WINE GV
76 82.7 94 62.7 MVM 78.8 94
93.3 66.7 GM 83 94.7 96
81.3
C2-.6 .2 -.07 .771 6882.. -.72 .19 -.40 .54
9251 .38 .14 -.79 .46 11781
F-m/8 g?4 C2 0 1 2 2 1 1 3 1 2 5
2 3 8 1 2 10 1 1 11 1 5 16 1
2 18 1 5 23 1 1 24 1 1 25 2 1 26
2 1 27 1 2 29 4 1 30 2 1 31 2
1 32 1 1 33 3 2 ... 1s 65 1
X g?4 (F-MN)/8 0 2 2 2 1 2 4 2
1 5 1 3 8 2 3 11 1 1 12 3
2 14 4 1 15 3 1 16 3 1 17 2
1 18 3 1 19 6 1 20 3 1 21 3
1 22 2 1 23 5 1 24 4 1 25 3
1 26 6 1 27 3 1 28 1 1 29 6
1 30 3 1 31 2 1 32 3 1 33 3
1 34 1 2 36 3 1 37 1 1 38 2
1 39 3 1 40 5 1 41 1 1 42 6
1 43 1 1 44 3 2 46 5 1 47 1
1 48 3 1 49 1 1 50 2 1 51 1
1 52 1 1 53 1 1 54 1 1 55 1
1 56 3 1 57 3 2 59 1 2 61 1
1 62 3 3 65 2 9 74 1 4 78 1
3 81 1 2 83 1 3 86 1 2 88 1
2 90 1 1 91 1 4 95 1 2 97 1
1 98 1 2 100 1 4 104 1 3 107 1
0 1 1 1 1 4 5 1 1 ... 1s
46 4 3 49 1 7 56 1 2 58 1 3
61 1 4 65 1 1 66 1 3 69 1 2
71 1 6 77 1 3 80 1 3 83 1 3
86 1 14 100 1 3 103 1 2 105 1
3 108 2 4 112 1
___ 2M
C2 gp?8 (F-MN)/5 0 2 2 2 1 2 4 2
1 5 1 3 8 2 3 11 1 1 12 2
2 14 4 1 15 3 1 16 3 1 17 2
1 18 3 1 19 6 1 20 3 1 21 3
1 22 1 1 23 5 1 24 3 1 25 3
1 26 6 1 27 3 1 28 1 1 29 6
1 30 3 1 31 2 1 32 1 1 33 3
1 34 1 2 36 3 2 38 2 1 39 2
1 40 5 1 41 1 1 42 6 1 43 1
1 44 3 2 46 5 1 47 1 1 48 1
1 49 1 1 50 2 1 51 1 1 52 1
1 53 1 1 54 1 1 55 1 1 56 3
1 57 2 2 59 1 2 61 1 1 62 3
3 65 2 9 74 1 4 78 1 8 86 1
2 88 1 2 90 1 5 95 1 2 97 1
1 98 1 2 100 1 4 104 1
C21 0L 8M 0H

C1 43L 33M 55H
C22 2M 0H C23
g?4 F-MN/8 0 1 2 2 1 2 4 1
2 6 1 1 7 1 1 8 1 2 10 1
1 11 1 1 12 1 1 13 1 3 16 2 3 19
1 2 21 1 5 26 1 1 27 1 1 28 2
1 29 2 1 30 1 2 32 5 1 33 2 1 34
2 1 35 1 1 36 3 1 37 3 1 38 3
1 39 5 1 40 3 1 41 7 1 42 6 1 43
3 1 44 5 1 45 1 1 46 3 1 47 3
1 48 4 1 49 7 1 50 4 1 51 6 1 52
10 1 53 3 1 54 4 1 55 8 1 56 5
1 57 3 1 58 7 1 59 2 1 60 2 1 61
1 1 62 2 2 64 1 1 65 2 1 66 1
1 67 2
C21 g?4 F-M/4 0 1 1 1 1 3 4 1 3 7
2 1 8 2 1 9 1 2 11 1 2 13 4
1 14 2 1 15 4 1 16 1 2 18 2 1 19
3 1 20 1 1 21 2 1 22 6 2 24 2
1 25 3 1 26 1 2 28 2 2 30 1 1 31
1 2 33 1 4 37 1 1 38 2 1 39 2
1 40 1 1 41 1 1 42 1 1 43 2 1 44
1 1 45 2 1 46 1 1 47 1 1 48 1
1 49 2 2 51 2 4 55 1 1 56 8 1 57
4 1 58 4 1 59 2 1 60 1 1 61 1
2 63 5 2 65 1 2 67 2 1 68 1 3 71
1 1 72 4 1 73 8 1 74 5 1 75 1
8 83 3 1 84 3 1 85 2 1 86 1 99 3
C211 g?5 F-M)/4 0 1 6 6 2 1 7 2
5 12 1 1 13 4 1 14 1 1 15 4 2 17
1 1 18 2 1 19 2 2 21 2 1 22 3
1 23 1 1 24 3 4 28 1 14 42 1 2 44
1 1 45 1 3 48 2 2 50 1 5 55 1
2 57 1 1 58 1 5 63 1 1 64 1 7 71
1 11 82 1 16 98 2
GV
___5L .
C111 3L 23M 49H
___ 7M C2
___ 4M C3
___6M C4
___ 30L 1M 4H
C231 g?4 F-M/8 0 1 7 ... 1s 12 1
2 14 6 1 15 7 4 19 1 1 20 3 1 21
3 1 22 2 1 23 1 2 25 1 2 27 1
2 29 1 1 30 1 1 31 1 2 33 1 6 39
1 3 42 1 4 46 1 10 56 2
__20L 5M .
C1F-?/4 g?4
___14M 0H C1 C2
0 1 1 1 1 7 8 1 4 12 1 4 16
1 2 18 1 2 20 2 1 21 2 2 ...
1s2s 71 2 2 73 1 1 74 1 2 76 2
2 78 2 4 82 2 2 84 1 6 90 2 8 98
1 9 107 1 16 123 1
___ 5L 1M .
___ 4M .
___ 2L 1M .
C211 32L 13M 0H
___5L 1M
C11 43L 23M 53H
_30L 8H_ . 3L 2M
C212 g?5 F-M/3 0 1 20 20 1 8 28 1
1 29 2 9 38 1 11 49 1 5 54 1
11 65 1 10 75 2 3 78 1 11 89 1
7 96 1 2 98 1 2 100 1 11 111 2
1 112 1
___6M 2H
C212 7L 3M 10H
2L 2M 1H
__6L 3M .
__1L 2H
C111 F-?/4 g?4 0 1 16 16 3 1 17 2 1 18 9
1 19 3 2 21 5 6 27 3 1 28 5 1 29 14 1 30
1 8 38 2 2 40 15 1 41 3 4 45 3 2 47 2
19 66 3 21 87 1
___1L 4M 3H
___ __1L
___1L 1M 4H
___ 8H
43L 38M 55H C2 0L 14M 0H C1
___ 3L 2M 18H
1L 21M
43L 28M 55H C21
__ 1L 2M 20H
C213 4L 7M 38H
___4L 2M 8H
___ 8H

C214 0L 5M 7H
___ 2M 9H
___ ___ .
1H 2M
0L 10M 0H C22
___ __ 31H
___1L 2H
7
ABALONE
GM
ACR CONC IRIS SEEDS WINE ABAL GV 76 83 94
63 73 MVM 79 94 93 67 79 GM 83
95 96 81 81
0.39 0.57 0.10 -0.72 0.21 0.57 0.44
0.09 -0.69 0.24 0.77 0.61 0.17 0.01
2.19 0.58 0.48 0.17 0.64 3.8 0.55 0.46
0.16 0.68 3.81
g?3 200F-M 0 1 11 11 1 14 25 1 17 42
1 1 43 1 5 48 1 3 51 1 2 ... 67 2
1 68 2 1 69 3 2 ... 1s 92 1
1H
1M _
1H
X g?2 100(F-M) 3 2 3 6 1 2 8 1 1
9 2 3 12 1 3 15 2 1 16 1 2 18 2
1 19 1 1 20 2 1 21 3 1 22 2
1 23 1 1 24 6 1 25 1 1 26 1 2 28
3 1 29 2 1 30 2 2 32 3 1 33 2
1 34 3 1 35 5 1 36 4 1 37 4 1 38
3 1 39 5 1 40 3 1 41 2 1 42 1
1 43 2 1 44 3 1 45 4 1 46 2 1 47
3 1 48 3 1 49 1 1 50 3 1 51 1
1 52 1 1 53 7 1 54 4 1 55 3 1 56
3 1 57 4 1 58 2 1 59 1 1 60 3
1 61 4 1 62 2 2 64 2 1 65 1 1 66
1 2 68 3 1 69 2 1 70 1 4 74 1
2 76 1 3 79 2 1 80 2 3 83 2 2 85
1 4 89 1 13 102 1
0.25 0.30 -0.20 -0.90 0.18 -0.44 -0.37
-0.19 -0.79 0.81 -0.52 -0.42 -0.19 -0.72
0.83 C1 g?3 300(F-M) 0 1 1 1 1 2 3
2 1 4 1 1 5 1 1 6 2 1 7 1
3 10 1 1 11 1 3 14 3 2 16 2 1 17
1 1 18 2 2 20 1 2 22 1 1 23 2
1 24 1 1 25 2 1 26 3 1 27 1 1 28
2 1 29 1 2 31 1 1 32 1 3 35 1
1 36 1 2 38 1 3 41 1 3 44 3 1 45
1 1 46 2 2 48 1 1 49 1 1 50 2
2 52 2 1 53 1 1 54 1 1 55 1 4 59
2 1 60 1 4 64 1 1 65 1 1 66 1
1 67 2 2 69 2 1 70 2 1 71 2 2 73
1 1 74 1 1 75 2 1 76 2 1 77 1
1 78 3 2 80 1 1 81 3 2 83 2 1 84
1 1 85 1 1 86 1 2 88 1 1 89 1
1 90 1 2 92 1
2M 1H _
5M 12H _

6L .
1M _

3L .
30L 85M 12H C1

C1 g?3 100F-M 0 1 6 6 1 1 ...
1s 54 1 2 56 2 3... 71 2
7M 4H .
1H
20L 84M 11H C11 10L 1M 0H

12L 7M _

3L 4M _

C11 g?3 400F-M 0 1 1 1 1 4 5 1 3
8 4 1 9 1 3 12 2 2 .. 81 2 3 84
2 1 85 1
2M 1H _
4M 1H _
2L 0M 0H _

1L 19M 1H _

16M 8H C11
17L 78M 9H C111 3L

1.0 .00 .00 .00 10 .62 .41 .13 .65 46 .33 .29 .13
.89 56 C2 g?3 300F-M 0 1 8 8 1 1 9
1 2 11 1 1 12 1 1 13 3 1 14 1
2 16 2 1 17 1 1 18 3 2 20 2 1 21
1 3 24 1 1 25 1 2 27 2 1 28 1
1 29 2 1 30 1 1 31 1 2 33 2 1 34
1 1 35 1 2 37 1 1 38 3 1 39 1
1 40 1 5 45 1 1 46 1 2 48 1 6 54
1 4 58 1 1 59 1 3 62 1 1 63 1
1 64 1 4 68 1 1 69 1 14 83 1 3 86
1 23 109 1
7L 3M 0H _

C111 g?3 1500F-M 0 1 15 15 1 5 20 1
4 24 1 1 25 1 1 26 1 3 29 1
1 30 1 1 31 2 1 32 1 1 33 2
3 36 1 2 38 3 1 39 2 2 41 2
1 42 1 1 43 2 2 45 1 2 47 3
1 48 1 2 50 1 1 51 1 4 55 2
1 56 3 2 58 1 2 60 3 1 61 2
1 62 2 2 64 1 1 65 2 3 68 2
1 ... 112 1 4 116 2
.55 .43 .14 .27 .38 C11 g?3 1000(F-M) 0 1
10 10 1 7 17 1 2 19 1 8 27 1
9 36 1 11 47 2 2 49 1 3 52 2 4 56
1 4 60 1 2 62 1 2 64 1 7 71 3
1 72 1 5 77 2 4 81 1 3 84 1 6 90
1
3L _

3M _

6L 8M 0H _

17M 2H .
13M 5H _
1M 2H _
4L 3M _

0M 6H _
1M 2H _
4L 72M 15H C1 10L 1M 0H

3M 1H _
2L 21M 1H _

12M 7H _
3L 13M 2H
15H _
1L 7M _

5M 10H _

1M _

4L 8M 4H

1H

6M 5H _
3L 30M 1H
1M 1H _ 1H

3L 51M 3H

8
gp1 Ct8 C16
. outliers. Some of them are substantial

MVM gapsgt6avg
KOSblogs dUnitSTDVec ggt6avg
3364 1804 185.38 0.56 0 3365 3399 186.38
1.00 1 3366 980 186.68 0.30 0 3367
1518 187.84 1.15 1 3368 2090 188.45 0.61
1 3369 890 189.10 0.65 1 3370 24
189.74 0.65 1 3371 2435 189.77 0.03
0 3372 804 190.14 0.36 0 3373 930
190.24 0.11 0 3374 1096 191.30 1.06
1 3375 1441 191.39 0.09 0 3376 2885
191.86 0.47 0 3377 2315 191.91 0.05
0 3378 699 192.04 0.13 0 3379 2108
194.34 2.30 1 3380 1316 195.58 1.24
1 3381 991 195.85 0.27 0 3382 1564
196.05 0.20 0 3383 2800 196.37 0.32
0 3384 880 196.62 0.25 0 3385 2038
196.75 0.13 0 3386 481 197.09 0.34
0 3387 480 197.85 0.76 1 3388 295
198.38 0.53 0 3389 1234 200.42 2.04
1 3390 2140 201.46 1.04 1 3391 3353
202.36 0.90 1 3392 3402 202.64 0.28
0 3393 45 202.86 0.21 0 3394 3017
204.63 1.77 1 3395 3365 207.54 2.91
1 3396 2436 207.77 0.24 0 3397 553
209.73 1.96 1 3398 2545 210.52 0.79
1 3399 54 213.63 3.11 1 3400 1933
214.58 0.95 1 3401 3201 216.16 1.57
1 3402 2895 217.18 1.02 1 3403 446
217.83 0.65 1 3404 2302 218.43 0.61
1 3405 2873 219.47 1.04 1 3406 3388
223.00 3.52 1 3407 1509 225.98 2.99
1 3408 32 229.46 3.48 1 3409 3189
231.30 1.84 1 3410 3228 231.43 0.13
0 3411 2107 232.39 0.96 1 3412 1150
232.79 0.40 0 3413 2279 236.69 3.90
1 3414 2289 237.43 0.74 1 3415 2385
238.03 0.60 0 3416 1037 245.93 7.90
1 3417 201 246.72 0.79 1 3418 1252
249.23 2.51 1 3419 1739 250.34 1.11
1 3420 2446 257.59 7.26 1 3421 1637
258.64 1.05 1 3422 3220 260.55 1.91
1 3423 1304 262.67 2.12 1 3424 2355
271.20 8.53 1 3425 232 293.86 22.66
1 3426 3411 299.23 5.37 1 3427 1955
303.42 4.19 1 3428 1832 328.03 24.61
1 3429 1197 335.83 7.81 1 3430 2852
364.01 28.18 1
AvgGp.0085 gpgt6avg ROW KOS F GAP
CT 1 1791 0.2270 --- -- 2 1317 0.2920
0.065 1 2668 1602 6.6576 0.007 2667 3090 1390
9.8504 0.004 422 3132 1546 10.278 0.012
42 3148 2662 10.507 0.021 16 3216 505 11.289
0.019 68 3264 2219 11.994 0.027 48 3291 231
12.445 0.039 27 3302 710 12.631 0.038
11 3317 220 12.934 0.023 15 3338 405 13.315
0.028 21 3355 194 13.693 0.009 17 3368 12
14.151 0.078 8 3378 2731 14.590 0.011
10 3392 1096 15.459 0.022 5
0.1AvgGp 64gaps Row
Doc F 28.2MxGp .6GapThreshold 1
1791 5.67 Gap 0 ... ... ... ...
... 8 3389 7.00 0.19 0 9 2397
7.65 0.65 1 10 2841 7.82 0.17 0
... ... ... ... ... 2621 2334 89.40
0.06 0 2622 1122 90.00 0.60 1 2623
245 90.06 0.06 0 ... ... ... ...
... 3123 3169 132.06 0.00 0 3124 321
132.81 0.75 1 3125 2047 133.05 0.24
0 ... ... ... ... ... 3210 343
145.29 0.37 0 3211 2475 145.89 0.60
1 3212 458 146.10 0.21 0 ... ...
... ... ... 3240 542 151.15 0.09 0
3241 2569 151.76 0.61 1 3242 1143 151.92
0.15 0 ... ... ... ... ... 3285
1803 157.97 0.00 0 3286 2257 158.70 0.73
1 3287 2723 158.77 0.07 0 ... ...
... ... ... 3293 129 159.56 0.32 0
3294 2541 160.45 0.89 1 3295 2870 160.48
0.03 0 ... ... ... ... ... 3301
401 161.38 0.04 0 3302 2918 162.03 0.65
1 3303 100 162.07 0.04 0 ... ...
... ... ... 3312 1157 164.54 0.08 0
3313 185 165.26 0.72 1 3314 685 165.91
0.65 1 3315 2948 166.25 0.34 0 ...
... ... ... ... 3325 190 168.59 0.37
0 3326 2498 169.20 0.61 1 3327 264
169.31 0.11 0 3328 1611 169.64 0.33
0 3329 3052 169.96 0.32 0 3330 1002
170.43 0.47 0 3331 1628 170.64 0.20
0 3332 1241 171.80 1.16 1 3333 3155
172.00 0.20 0 ... ... ... ...
... 3342 861 173.84 0.15 0 3343 2509
174.98 1.13 1 3344 2293 175.65 0.67
1 3345 1257 175.67 0.02 0 3346 2776
176.04 0.37 0 3347 1422 177.15 1.11
1 3348 12 177.24 0.09 0 3349 183
177.26 0.02 0 3350 620 177.29 0.03
0 3351 679 179.08 1.79 1 3352 462
179.15 0.07 0 3353 3404 180.02 0.88
1 3354 1850 180.79 0.76 1 3355 3342
181.21 0.43 0 3356 1396 183.04 1.82
1 3357 2982 183.26 0.22 0
___
___ gap.65 Ct9 C1

___
___ gap.6 Ct2613 C2

___
___ gap.75 Ct 502 C3

___
___ gap.6 Ct 87 C4

___
___ gap.61 Ct30 C5

___
___ gap.73 Ct45 C6

___
___ gap.89 Ct8 C7

___
___ gap.65 Ct8 C8

___
___ gp.72 Ct 11 C9

___
___ gp.65 Ct1 outlr

___
___ gp.61 Ct12 C11

___
___ gp1.2 Ct6 C12

___
___ gp1.1 Ct11 C13

___
___ gap.67 Ct1 utlr

___
___ gp1.1 Ct3 C15

___
___ gp1.8 Ct4 C16

___
___ gp1.8 Ct5 otlr

9
GV using a grid (Unitized Corners of Unit Cube
Diagonal of the Variance Matrix
Mean-to-Vector_of_Medians)
On these pages we display the variance hill-climb
for each of the four datasets (Concrete, IRIS,
Seeds, Wine) for a grid of starting unit vectors,
d. I took the circumscribing unit non-negative
cube and used all the Unitized diagonals. In
low dimension (all dimension4 here) this grid is
very nearly a uniform grid. Note that this will
work less and less well as the dimension grows.
In all cases, the same local max and nearly the
same unit vector are reached.
10
GV using a grid (Unitized Corners of Unit Cube
Diagonal of the Variance Matrix
Mean-to-Vector_of_Medians) 2
As we all know, Dr. Ubhaya is the best
Mathematician on campus and he is attempting to
prove three things 1. That a GV-hill-climb that
does not reach the global max Variance is rare
indeed. 2. That one is guaranteed to reach the
global maximum with at least one of the
coordinate unit vectors (so a 90 degree grid will
always suffice). 3. That akk will always reach
the global max.
11
Finding round clusters that aren't DPPd
separable? (no linear gap)
Find the golf ball? Suppose we have a white mask
pTree. No linear gaps exits to reveal it.
Search a grid of d-tubes until a DPPd gap is
found in the interior of the tube (Form mask
pTree for interior of the d-tube. Apply DPPd
that mask to reveal interior gaps.)
Look for conical gaps (fix the the cone point at
the middle of tube) over all cone angles (look
for an interval of angles with no points).
Notice that this method includes DPPd since a gap
for a cone angle of 90 degrees is linear.
12
FAUST Clustering using Fpq(x)RND(x-p)o(q-p)/q-p
-minF on Spaeth image (pavg
X x1 x2 1 2 3 4 5 6 7 8 9 a b 1 1 1 1q 3
1 2 3 2 2 3 2 4 3 3 4 5 2 5 5 9
3 6 15 1 7 f 14 2 8 15 3 9
6 p d 13 4 a
b 10 9 b c e 1110 c 9 11
d a 1111 e 8 7 8 f 7 9
The 15 Value_Arrays (one for each
qz1,z2,z3,...) z1 0 1 2 5 6 10 11 12 14 z2
0 1 2 5 6 10 11 12 14 z3 0 1 2 5 6 10 11
12 14 z4 0 1 3 6 10 11 12 14 z5 0 1 2 3
5 6 10 11 12 14 z6 0 1 2 3 7 8 9 10 z7 0
1 2 3 4 6 9 11 12 z8 0 1 2 3 4 6 9
11 12 z9 0 1 2 3 4 6 7 10 12 13 za 0 1
2 3 4 5 7 11 12 13 zb 0 1 2 3 4 6 8 10
11 12 zc 0 1 2 3 5 6 7 8 9 11 12 13 zd
0 1 2 3 7 8 9 10 ze 0 1 2 3 5 7 9 11
12 13 zf 0 1 3 5 6 7 8 9 10 11
The 15 Count_Arrays z1 2 2 4 1 1 1 1 2
1 z2 2 2 4 1 1 1 1 2 1 z3 1 5 2 1 1
1 1 2 1 z4 2 4 2 2 1 1 2 1 z5 2 2
3 1 1 1 1 1 2 1 z6 2 1 1 1 1 3 3
3 z7 1 4 1 3 1 1 1 2 1 z8 1 2 3 1 3
1 1 2 1 z9 2 1 1 2 1 3 1 1 2 1 za
2 1 1 1 1 1 4 1 1 2 zb 1 2 1 1 3 2
1 1 1 2 zc 1 1 1 2 2 1 1 1 1 1 1
2 zd 3 3 3 1 1 1 1 2 ze 1 1 2 1 3 2
1 1 2 1 zf 1 2 1 1 2 1 2 2 2 1
gap F6, F10
gap F2, F5
pTree masks of the 3 z1_clusters (obtained by
ORing)
z12 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1
z11 0 0 0 0 0 0 1 1 1 1 1 1 1 1 0
z13 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0
The FAUST algorithm
1. project onto each pq line using the dot
product with the unit vector from p to q.
2. Generate ValueArrays (also generate the
CountArray and the mask pTrees).
3. Analyze all gaps and create sub-cluster pTree
Masks.
13
FAUST Gap Revealer
Width ? 24 so compute all pTree combinations
down to p4 and p'4 dM-p
1 z1 z2 z7 2 z3 z5
z8 3 z4 z6 z9 4
za 5 M 6
7 8 zf 9
zb a zc b
zd ze c 0 1 2 3 4 5 6 7 8 9 a b c d e f
Z z1 1 1 z2 3 1 z3 2 2 z4 3 3 z5 6
2 z6 9 3 z7 15 1 z8 14 2 z9 15 3 za 13 4 zb
10 9 zc 11 10 zd 9 11 ze 11 11 zf 7 8
Fzod 11 27 23 34 53 80 118 114 125 114 110
121 109 125 83
p6 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1
p5 0 0 0 1 1 0 1 1 1 1 1 1 1 1 0
p4 0 1 1 0 1 1 1 1 1 1 0 1 0 1 1
p3 1 1 0 0 0 0 0 0 1 0 1 1 1 1 0
p2 0 0 1 0 1 0 1 0 1 0 1 0 1 1 0
p1 1 1 1 1 0 0 1 1 0 1 1 0 0 0 1
p0 1 1 1 0 1 0 0 0 1 0 0 1 1 1 1
p6' 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0
p5' 1 1 1 0 0 1 0 0 0 0 0 0 0 0 1
p4' 1 0 0 1 0 0 0 0 0 0 1 0 1 0 0
p3' 0 0 1 1 1 1 1 1 0 1 0 0 0 0 1
p2' 1 1 0 1 0 1 0 1 0 1 0 1 0 0 1
p1' 0 0 0 0 1 1 0 0 1 0 0 1 1 1 0
p0' 0 0 0 1 0 1 1 1 0 1 1 0 0 0 0
p

011 0000, 011 1111 48, 64). z5od53 is 19
from z4od34 (gt24) but 11 from 64. But the next
int 64,80) is empty z5 is ?27 from its right
nbr. z5 is declared an outlier and we put a
subcluster cut thru z5
000 0000, 000 1111 0,150,16) has 1 point,
z1. This is a 24 thinning. z1od11 is only 5
units from the right edge, so z1 is not declared
an outlier) Next, we check the min dis from the
right edge of the next interval to see if z1's
right-side gap is actually ? 24 (the calculation
of the min is a pTree process - no x looping
required!)
001 0000, 001 1111 16,32). The minimum,
z3od23 is 7 units from the left edge, 16, so z1
has only a 5712 unit gap on its right (not a 24
gap). So z1 is not declared a 24 (and is
declared a 24 inlier).
010 0000 , 010 1111 32,48). z4od34 is
within 2 of 32, so z4 is not declared an anomaly.
111 0000 , 111 1111 112,128)
z7od118 z8od114 z9od125 zaod114 zcod121 zeod
125 No 24 gaps. But we can consult SpS(d2(x,y)
for actual distances
110 0000 , 110 1111 96,112). zbod110,
zdod109. So both z6,zf declared outliers
(gap?16 both sides.
100 0000 , 100 1111 64, 80). This is clearly
a 24 gap.
101 0000 , 101 1111 80, 96). z6od80, zfod83
Which reveals that there are no 24 gaps in this
subcluster. And, incidentally, it reveals a 5.8
gap between 7,8,9,a and b,c,d,e but that
analysis is messy and the gap would be revealed
by the next xofM round on this sub-cluster anyway.
X1 X2 dX1X2 z7 z8 1.4 z7 z9 2.0 z7 z10
3.6 z7 z11 9.4 z7 z12 9.8 z7 z13 11.7 z7
z14 10.8 z8 z9 1.4 z8 z10 2.2 z8 z11
8.1 z8 z12 8.5 z8 z13 10.3 z8 z14 9.5
X1 X2 dX1X2 z9 z10 2.2 z9 z11 7.8 z9 z12
8.1 z9 z13 10.0 z9 z14 8.9 z10 z11 5.8 z10
z12 6.3 z10 z13 8.1 z10 z14 7.3
X1 X2 dX1X2 z11 z12 1.4 z11 z13 2.2 z11 z14
2.2 z12 z13 2.2 z12 z14 1.0 z13 z14 2.0
14
FAUST Tube Clustering (This method attempts to
build tubular-shaped gaps around clusters)
q
Allows for a better fit around convex clusters
that are elongated in one direction (not round).
Exhaustive Search for all tubular gaps It takes
two parameters for a pseudo- exhaustive search
(exhaustive modulo a grid width). 1. A
StartPoint, p (an n-vector, so n
dimensional) 2. A UnitVector, d (a n-direction,
so n-1 dimensional - grid on the surface of
sphere in Rn). Then for every choice of (p,d)
(e.g., in a grid of points in R2n-1) two
functionals are used to enclose subclusters in
tubular gaps. a. SquareTubeRadius functional,
STR(y) (y-p)o(y-p) - ((y-p)od)2 b.
TubeLength functional, TL(y) (y-p)od
Given a p, do we need a full grid of ds
(directions)? No! d and -d give the same
TL-gaps.
Given d, do we need a full grid of p starting
pts? No! All p' s.t. p'pcd give same
gaps. Hill climb gap width from a good starting
point and direction.
MATH Need dot product projection length and dot
product projection distance (in red).
p
dot product projection distance
That is, we needed to compute the green constants
and the blue and red dot product functionals in
an optimal way (and then do the PTreeSet
additions/subtractions/multiplications). What is
optimal? (minimizing PTreeSet functional
creations and PTreeSet operations.)
15
xs2 cone.1 39 2 40 1 41 1 44 1 45
1 46 1 47 1 52 1 i39 59 2 60 4 61
3 62 6 63 10 64 10 65 5 66 4 67 4 69
1 70 1 59
w maxs-to-mins cone.939 14 1 i25 16 1
i40 18 2 i16 i42 19 2 i17 i38 20 2 i11
i48 22 2 23 1 24 4 i34 i50 25 3 i24
i28 26 3 i27 27 5 28 3 29 2 30 2 31
3 32 4 34 3 35 4 36 2 37 2 38 2 39
3 40 1 41 2 46 1 47 2 48 1 49 1
i39 53 1 54 2 55 1 56 1 57 8 58 5 59
4 60 7 61 4 62 5 63 5 64 1 65 3 66
1 67 1 68 1 114 14 i and 100 s/e. So picks
i as 0
w naaa-xaaa cone.95 12 1 13 2 14 1 15
2 16 1 17 1 18 4 19 3 20 2 21 3 22
5 23 6 i21 24 5 25 1 27 1 28 1 29
2 30 2 i7 41/43 e so picks e
Cone Clustering (finding cone-shaped clusters)
xs1 cone1/v2 60 3 61 4 62 3 63 10
64 15 65 9 66 3 67 1 69 2 50
xs2 cone1/v2 47 1 59 2 60 4 61 3 62
6 63 10 64 10 65 5 66 4 67 4 69 1 70
1 51
xs2 cone.9 59 2 60 3 61 3 62 5 63
9 64 10 65 5 66 4 67 4 69 1 70 1 47
w maxs cone.707 0 2 8 1 10 3 12 2 13
1 14 3 15 1 16 3 17 5 18 3 19 5 20
6 21 2 22 4 23 3 24 3 25 9 26 3 27
3 28 3 29 5 30 3 31 4 32 3 33 2 34
2 35 2 36 4 37 1 38 1 40 1 41 4 42
5 43 5 44 7 45 3 46 1 47 6 48 6 49
2 51 1 52 2 53 1 55 1 137
w maxs cone.93 8 1 i10 13 1 14 3 16
2 17 2 18 1 19 3 20 4 21 1 24 1 25
4 26 1 e21 e34 27 2 29 2 37 1 i7 27/29
are i's
F(y-M)o(x-M)/x-M-mn restricted to a cosine
cone on IRIS
w aaan-aaax cone.54 7 3 i27 i28 8 1 9
3 10 12 i20 i34 11 7 12 13 13 5 14 3 15
7 19 1 20 1 21 7 22 7 23 28 24
6 100/104 s or e so 0 picks i
xi1 cone.707 34 1 35 1 36 2 37 2 38
3 39 5 40 4 42 6 43 2 44 7 45 5 47
2 48 3 49 3 50 3 51 4 52 3 53 2 54
2 55 4 56 2 57 1 58 1 59 1 60 1 61
1 62 1 63 1 64 1 66 1 75
xe1 cone.707 33 1 36 2 37 2 38 3 39
1 40 5 41 4 42 2 43 1 44 1 45 6 46
4 47 5 48 1 49 2 50 5 51 1 52 2 54
2 55 1 57 2 58 1 60 1 62 1 63 1 64
1 65 2 60
Cosine conical gapping seems quick and easy
(cosine dot product divided by both lengths.
Length of the fixed vector, x-M, is a one-time
calculation. Length y-M changes with y so build
the PTreeSet.
w maxs cone.925 8 1 i10 13 1 14 3 16
3 17 2 18 2 19 3 20 4 21 1 24 1 25
5 26 1 e21 e34 27 2 28 1 29 2 31 1
e35 37 1 i7 31/34 are i's
w xnnn-nxxx cone.95 8 2 i22 i50 10 2 11
2 i28 12 4 i24 i27 i34 13 2 14 4 15 3 16
8 17 4 18 7 19 3 20 5 21 1 22 1 23
1 34 1 i39 43/50 e so picks out e
16
Separate classr, classv using midpoints of means
FAUST Classifier
PrP(xod)lta
PvP(xod)?a
Set a (mR(mV-mR)/2)od (mRmV)/2 o d ?
where D mR?mV dD/D
Training amounts to choosing the Cut hyperplane
(n-1)-dimensionl hyperplane (and thus cuts the
space in two). Classify with one horizontal
program (AND/OR) across the pTrees to get a mask
pTree for each class (bulk classification). Improv
e accuracy? e.g., by considering the
dispersion within classes. Use 1.
vector_of_medians (vomv (median(v1),
median(v2),...)) instead of means then use stdev
ratio to place the cut. 2. Cut at Midpt of
Maxrod, Minvod. If there is no gap, move
Cut until r_errors v_errors is minimized. 3.
Hill-climb d to maximize gap (or minimize errors
when applied to the training set). 4. Replace mr,
mv with the avg of the margin points? 5. Round
classes expected? use SDmr lt D/2 for r-class
and SDmv ltD/2 for v-class.
dim 2
r   r vv r mR   r
v v v v       r    r      v
mV
v      r    v v     r
v
dim 1
17
"Gap Hill Climbing" mathematical analysis
rotation d toward a higher F-STD or grow 1 gap
using support pairs
F-slices are hyperplanes (assuming Fdotd) so it
would makes sense to try to "re-orient" d so that
the gap grows. Instead of taking the "improved"
p and q to be the means of the entire
n-dimensional half-spaces which is cut by the gap
(or thinning), take as p and q to be the means of
the F-slice (n-1)-dimensional hyperplanes
defining the gap or thinning. This is easy since
our method produces the pTree mask the sequence
of F-values and the sequence of counts of points
that give us those value that we use to find
large gaps in the first place.
Dot F paaan qaaax 0 6 1 28 2 7 3
7 4 1 5 1 9 7 10 3 11 5 12 13 13
8 14 12 15 4 16 2 17 12 18 5 19 6 20
6 21 3 22 8 23 3 24 3
C1lt7 (50 Set)
d2-gap gtgt than d1gap (still not optimal.)
Weight mean by the dist from gap? (d-barrel
radius)
7ltC2lt16 (4i, 48e)
In this example it seems to make for a larger
gap, but what weightings should be used? (e.g.,
1/radius2) (zero weighting after the first gap is
identical to the previous). Also we really want
to identify the Support vector pair of the gap
(the pair, one from one side and the other from
the other side which are closest together) as p
and q (in this case, 9 and a but we were just
lucky to draw our vector through them.) We could
check the d-barrel radius of just these gap slice
pairs and select the closest pair as p and q???
C3gt16 (46i, 2e)
hill-climb gap at 16 w half-space avgs.
C2uC3 pavglt16 qavggt16 0 1 1 1 2 2 3
1 7 2 9 2 10 2 11 3 12 3 13 2 14
5 15 1 16 3 17 3 18 2 19 2 20 4 21
5 22 2 23 5 24 9 25 1 26 1 27 3 28
2 29 1 30 3 31 5 32 2 33 3 34 3 35
1 36 2 37 4 38 1 39 1 42 2 44 1 45
2 47 2
No conclusive gaps Sparse Lo end Check 0,9
0 1 2 2 3 7 7 9 9 i39
e49 e8 e44 e11 e32 e30 e15 e31 i39 0 17 21
21 24 22 19 19 23 e49 17 0 4 4 7
8 8 9 9 e8 21 4 0 1 5 7 8 10
8 e44 21 4 1 0 4 6 8 9 7 e11
24 7 5 4 0 7 9 11 7 e32 22 8
7 6 7 0 3 6 1 e30 19 8 8 8 9
3 0 4 4 e15 19 9 10 9 11 6 4
0 6 e31 23 9 8 7 7 1 4 6
0 i39,e49,e11 singleton outliers. e8,i44
doubleton outlier set
There is a thinning at 22 and it is the same one
but it is not more prominent. Next we attempt to
hill-climb the gap at 16 using the mean of the
half-space boundary. (i.e., p is avg14 q is
avg17.
Sparse Hi end Check 38,47 di
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