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MS²PIP timsTOF prediction models
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MS²PIP timsTOF prediction models
Newly trained peak intensity prediction models for data from timsTOF instruments
Arthur Declercq
Created on October 11
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Last edited on October 24
Comment
b
y
datas...
0
1
2
3
4
5
6
7
8
9
10
alpha
0.50
0.55
0.60
0.65
0.70
0.75
0.80
0.85
0.90
0.95
1.00
colsa...
0
1
2
3
4
5
6
7
8
9
10
gamma
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
lambda
0
50
100
150
200
250
300
350
400
450
500
min_c...
2
3
4
5
6
7
8
9
10
11
12
13
14
15
max_d...
0.50
0.55
0.60
0.65
0.70
0.75
0.80
0.85
0.90
0.95
1.00
subsa...
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
itera...
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
eta
0.0005
0.0010
0.0015
0.0020
0.0025
0.0030
0.0035
0.0040
test_...
1.05
1.10
1.15
1.20
1.25
1.30
1.35
1.40
1.45
1.50
1.55
1.60
1.65
1.70
1.75
best_...
train_rmse_avg and max_leaves v. test_rmse_avg
train_rmse_avg and max_leaves v. test_rmse_avg
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
max_leaves
1.0
1.1
1.2
1.3
1.4
1.5
1.6
1.7
test_rmse_avg
1
1.2
1.4
1.6
train_rmse_avg
Run set
100
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