Mercurial > repos > jjkoehorst > sapp
comparison rnaseq/cutadapt/test-data/lps_arrhythmia_log.txt @ 11:a712b378e090
cutadapt added
author | jjkoehorst <jasperkoehorst@gmail.com> |
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date | Sat, 21 Feb 2015 16:33:42 +0100 |
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10:3378d12591ea | 11:a712b378e090 |
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1 Data set has 452 vectors with 279 features. | |
2 Sampled 452 points out of 452 | |
3 calculateLambdaMax: n=279, m=452, m+=245, m-=207 | |
4 computed value of lambda_max: 1.8231e+02 | |
5 | |
6 **** Initial point: nz=0, f= 0.69314718056, lambda= 1.641e+02 | |
7 iter 1, gpnorm=4.2035e-02, nonzero= 1 ( 0.4%), function=6.931471805599e-01, alpha=1.0000e+00 | |
8 iter 2, gpnorm=1.9781e-02, nonzero= 1 ( 0.4%), function=6.903943411116e-01, alpha=8.0000e-01 | |
9 iter 3, gpnorm=6.0325e-03, nonzero= 1 ( 0.4%), function=6.896822613633e-01, alpha=6.4000e-01 | |
10 iter 4, gpnorm=7.2193e-04, nonzero= 1 ( 0.4%), function=6.896101060279e-01, alpha=5.1200e-01 | |
11 iter 5, gpnorm=1.0530e-05, nonzero= 1 ( 0.4%), function=6.896090566277e-01, alpha=4.0960e-01 | |
12 iter 6, gpnorm=1.7618e-09, nonzero= 1 ( 0.4%), function=6.896090564044e-01, alpha=3.2768e-01 | |
13 Function evals = 12, Gradient evals = 6.0 | |
14 | |
15 **** Initial point: nz=1, f= 0.689609056404, lambda= 1.168e+02 | |
16 iter 1, gpnorm=1.7618e-09, nonzero= 1 ( 0.4%), function=6.896090564044e-01, alpha=3.2768e-01 | |
17 Function evals = 2, Gradient evals = 1.0 | |
18 | |
19 **** Initial point: nz=1, f= 0.689609056404, lambda= 8.310e+01 | |
20 iter 1, gpnorm=1.7618e-09, nonzero= 1 ( 0.4%), function=6.896090564044e-01, alpha=3.2768e-01 | |
21 Function evals = 2, Gradient evals = 1.0 | |
22 | |
23 **** Initial point: nz=1, f= 0.689609056404, lambda= 5.914e+01 | |
24 iter 1, gpnorm=1.7618e-09, nonzero= 1 ( 0.4%), function=6.896090564044e-01, alpha=3.2768e-01 | |
25 Function evals = 2, Gradient evals = 1.0 | |
26 | |
27 **** Initial point: nz=1, f= 0.689609056404, lambda= 4.209e+01 | |
28 iter 1, gpnorm=1.7618e-09, nonzero= 1 ( 0.4%), function=6.896090564044e-01, alpha=3.2768e-01 | |
29 Function evals = 2, Gradient evals = 1.0 | |
30 | |
31 **** Initial point: nz=1, f= 0.689609056404, lambda= 2.996e+01 | |
32 iter 1, gpnorm=1.7618e-09, nonzero= 1 ( 0.4%), function=6.896090564044e-01, alpha=3.2768e-01 | |
33 Function evals = 2, Gradient evals = 1.0 | |
34 | |
35 **** Initial point: nz=1, f= 0.689609056404, lambda= 2.132e+01 | |
36 iter 1, gpnorm=1.7618e-09, nonzero= 1 ( 0.4%), function=6.896090564044e-01, alpha=3.2768e-01 | |
37 Function evals = 2, Gradient evals = 1.0 | |
38 | |
39 **** Initial point: nz=1, f= 0.689609056404, lambda= 1.517e+01 | |
40 iter 1, gpnorm=1.7618e-09, nonzero= 1 ( 0.4%), function=6.896090564044e-01, alpha=3.2768e-01 | |
41 Function evals = 2, Gradient evals = 1.0 | |
42 | |
43 **** Initial point: nz=1, f= 0.689609056404, lambda= 1.080e+01 | |
44 iter 1, gpnorm=1.7618e-09, nonzero= 1 ( 0.4%), function=6.896090564044e-01, alpha=3.2768e-01 | |
45 Function evals = 2, Gradient evals = 1.0 | |
46 | |
47 **** Initial point: nz=1, f= 0.689609056404, lambda= 7.685e+00 | |
48 iter 1, gpnorm=1.7618e-09, nonzero= 1 ( 0.4%), function=6.896090564044e-01, alpha=3.2768e-01 | |
49 Function evals = 2, Gradient evals = 1.0 | |
50 | |
51 **** Initial point: nz=1, f= 0.689609056404, lambda= 5.469e+00 | |
52 iter 1, gpnorm=1.7618e-09, nonzero= 1 ( 0.4%), function=6.896090564044e-01, alpha=3.2768e-01 | |
53 Function evals = 2, Gradient evals = 1.0 | |
54 | |
55 lambda=1.64e+02 solution: | |
56 optimal log-likelihood function value: 6.90e-01 | |
57 optimal *regularized* log-likelihood function value: 6.90e-01 | |
58 number of non-zeros at the optimum: 1 | |
59 number of iterations required: 6 | |
60 prediction using this solution: | |
61 54.20% of vectors were correctly predicted. | |
62 245 correctly predicted. | |
63 207 in +1 predicted to be in -1. | |
64 0 in -1 predicted to be in +1. | |
65 0 in +1 with 50/50 chance. | |
66 0 in -1 with 50/50 chance. | |
67 | |
68 lambda=1.17e+02 solution: | |
69 optimal log-likelihood function value: 6.90e-01 | |
70 optimal *regularized* log-likelihood function value: 6.90e-01 | |
71 number of non-zeros at the optimum: 1 | |
72 number of iterations required: 1 | |
73 prediction using this solution: | |
74 54.20% of vectors were correctly predicted. | |
75 245 correctly predicted. | |
76 207 in +1 predicted to be in -1. | |
77 0 in -1 predicted to be in +1. | |
78 0 in +1 with 50/50 chance. | |
79 0 in -1 with 50/50 chance. | |
80 | |
81 lambda=8.31e+01 solution: | |
82 optimal log-likelihood function value: 6.90e-01 | |
83 optimal *regularized* log-likelihood function value: 6.90e-01 | |
84 number of non-zeros at the optimum: 1 | |
85 number of iterations required: 1 | |
86 prediction using this solution: | |
87 54.20% of vectors were correctly predicted. | |
88 245 correctly predicted. | |
89 207 in +1 predicted to be in -1. | |
90 0 in -1 predicted to be in +1. | |
91 0 in +1 with 50/50 chance. | |
92 0 in -1 with 50/50 chance. | |
93 | |
94 lambda=5.91e+01 solution: | |
95 optimal log-likelihood function value: 6.90e-01 | |
96 optimal *regularized* log-likelihood function value: 6.90e-01 | |
97 number of non-zeros at the optimum: 1 | |
98 number of iterations required: 1 | |
99 prediction using this solution: | |
100 54.20% of vectors were correctly predicted. | |
101 245 correctly predicted. | |
102 207 in +1 predicted to be in -1. | |
103 0 in -1 predicted to be in +1. | |
104 0 in +1 with 50/50 chance. | |
105 0 in -1 with 50/50 chance. | |
106 | |
107 lambda=4.21e+01 solution: | |
108 optimal log-likelihood function value: 6.90e-01 | |
109 optimal *regularized* log-likelihood function value: 6.90e-01 | |
110 number of non-zeros at the optimum: 1 | |
111 number of iterations required: 1 | |
112 prediction using this solution: | |
113 54.20% of vectors were correctly predicted. | |
114 245 correctly predicted. | |
115 207 in +1 predicted to be in -1. | |
116 0 in -1 predicted to be in +1. | |
117 0 in +1 with 50/50 chance. | |
118 0 in -1 with 50/50 chance. | |
119 | |
120 lambda=3.00e+01 solution: | |
121 optimal log-likelihood function value: 6.90e-01 | |
122 optimal *regularized* log-likelihood function value: 6.90e-01 | |
123 number of non-zeros at the optimum: 1 | |
124 number of iterations required: 1 | |
125 prediction using this solution: | |
126 54.20% of vectors were correctly predicted. | |
127 245 correctly predicted. | |
128 207 in +1 predicted to be in -1. | |
129 0 in -1 predicted to be in +1. | |
130 0 in +1 with 50/50 chance. | |
131 0 in -1 with 50/50 chance. | |
132 | |
133 lambda=2.13e+01 solution: | |
134 optimal log-likelihood function value: 6.90e-01 | |
135 optimal *regularized* log-likelihood function value: 6.90e-01 | |
136 number of non-zeros at the optimum: 1 | |
137 number of iterations required: 1 | |
138 prediction using this solution: | |
139 54.20% of vectors were correctly predicted. | |
140 245 correctly predicted. | |
141 207 in +1 predicted to be in -1. | |
142 0 in -1 predicted to be in +1. | |
143 0 in +1 with 50/50 chance. | |
144 0 in -1 with 50/50 chance. | |
145 | |
146 lambda=1.52e+01 solution: | |
147 optimal log-likelihood function value: 6.90e-01 | |
148 optimal *regularized* log-likelihood function value: 6.90e-01 | |
149 number of non-zeros at the optimum: 1 | |
150 number of iterations required: 1 | |
151 prediction using this solution: | |
152 54.20% of vectors were correctly predicted. | |
153 245 correctly predicted. | |
154 207 in +1 predicted to be in -1. | |
155 0 in -1 predicted to be in +1. | |
156 0 in +1 with 50/50 chance. | |
157 0 in -1 with 50/50 chance. | |
158 | |
159 lambda=1.08e+01 solution: | |
160 optimal log-likelihood function value: 6.90e-01 | |
161 optimal *regularized* log-likelihood function value: 6.90e-01 | |
162 number of non-zeros at the optimum: 1 | |
163 number of iterations required: 1 | |
164 prediction using this solution: | |
165 54.20% of vectors were correctly predicted. | |
166 245 correctly predicted. | |
167 207 in +1 predicted to be in -1. | |
168 0 in -1 predicted to be in +1. | |
169 0 in +1 with 50/50 chance. | |
170 0 in -1 with 50/50 chance. | |
171 | |
172 lambda=7.68e+00 solution: | |
173 optimal log-likelihood function value: 6.90e-01 | |
174 optimal *regularized* log-likelihood function value: 6.90e-01 | |
175 number of non-zeros at the optimum: 1 | |
176 number of iterations required: 1 | |
177 prediction using this solution: | |
178 54.20% of vectors were correctly predicted. | |
179 245 correctly predicted. | |
180 207 in +1 predicted to be in -1. | |
181 0 in -1 predicted to be in +1. | |
182 0 in +1 with 50/50 chance. | |
183 0 in -1 with 50/50 chance. | |
184 | |
185 lambda=5.47e+00 solution: | |
186 optimal log-likelihood function value: 6.90e-01 | |
187 optimal *regularized* log-likelihood function value: 6.90e-01 | |
188 number of non-zeros at the optimum: 1 | |
189 number of iterations required: 1 | |
190 prediction using this solution: | |
191 54.20% of vectors were correctly predicted. | |
192 245 correctly predicted. | |
193 207 in +1 predicted to be in -1. | |
194 0 in -1 predicted to be in +1. | |
195 0 in +1 with 50/50 chance. | |
196 0 in -1 with 50/50 chance. | |
197 |