-
Notifications
You must be signed in to change notification settings - Fork 86
/
DatasetConfig.yaml
131 lines (129 loc) · 3.39 KB
/
DatasetConfig.yaml
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
# Bandit Lib Config File
# Config file to set different parameters for the system
# To use append --config option to the python Simulation.py command
# i.e: python Simulation.py --config <config-file-name>.yaml
# None of the parameters are required, if not included system will
# default to a value
# Default values for the parameters are the current values for each parameter
# System level settings to be used in all algorithms
general:
context_dimension: 25 # (int) The number of features which the algorithm knows about each article
hidden_dimension: 0 # (int) The number of features hidden from the algorithms
pool_article_size: 20 # (int) Number of articles to select from total pool from which the algorithm can choose
plot: True # (True/False) Should plots be created
dataset: LastFM #(LastFM/Delicious/Yahoo) Choosing a dataset rather than simluation will override some of the other paramaters
# Parameters for the different algorithms
alg:
# General Parameters, setting in this section will overwrite default values in all algorithms simulation
general:
alpha: 0.3
lambda_: 0.1
# Define what sort of additional parameter modifications will be tracked
parameters:
Theta: True
CoTheta: False
W: False
V: False
# Specific Parameters, setting in this section under an algorithm will overwrite default and
# general parameters for that algorithm
specific:
LinUCB:
alpha: 0.3
lambda_: 0.1
parameters:
Theta: True
CoTheta: False
W: False
V: False
LinPHE:
a: 1
lambda_: 0.1
parameters:
Theta: True
CoTheta: False
W: False
V: False
ThompsonSampling:
lambda_: 0.1
R: .0001
delta: .1
epsilon: .05
parameters:
Theta: True
CoTheta: False
W: False
V: False
# CoLinUCB:
# alpha: 0.3
# lambda_: 0.1
# use_alpha_t: False # Use a theoretical alpha_t value
# parameters:
# Theta: False
# CoTheta: True
# W: False
# V: False
# GOBLin:
# alpha: 0.3
# lambda_: 0.1
# use_alpha_t: False
# parameters:
# Theta: False
# CoTheta: True
# W: False
# V: False
# HLinUCB:
# alpha: 0.3
# alpha2: 0.1
# lambda_: 0.1
# parameters:
# Theta: False
# CoTheta: True
# W: False
# V: True
# FairUCB:
# alpha: 0.3
# lambda_: 0.1
# parameters:
# Theta: True
# CoTheta: False
# W: False
# V: False
# UCBPMF:
# sigma : 0.5
# sigmaU : 1
# sigmaV : 1
# alpha : 0.1
# parameters:
# Theta: False
# CoTheta: False
# W: False
# V: False
# FactorUCB:
# alpha: 0.05
# alpha2: 0.025
# lambda_: 0.1
# parameters:
# Theta: False
# CoTheta: True
# W: False
# V: True
# CLUB:
# alpha: 0.1
# alpha2: 0.5
# lambda_: 0.1
# cluster_init : 'Erdos-Renyi'
# parameters:
# Theta: False
# CoTheta: False
# W: False
# V: False
# PTS:
# particle_num : 10
# sigma : 0.5
# sigmaU : 1
# sigmaV : 1
# parameters:
# Theta: False
# CoTheta: False
# W: False
# V: False