Hyperparameters for gru4rec (fixed layer size of 100)

We tested the following hyperparameter space:

Parameter From To Steps
Loss Function BPR-MAX TOP1-MAX -
Final Activation Function ELU-0.5 Linear -
Learning Rate 0.1
0.5		 0.01
0.1		 10
5
Momentum 0.00 0.90 0.10
Drop-Out 0.00 0.90 0.10
Constrained Embedding True False -

Dataset Loss Function Final Activation Function Learning Rate Momentum Drop-Out Constrained Embedding
RSC15 TOP1-MAX Linear 0.04 0.0 0.3 True
RETAILROCKET TOP1-MAX Linear 0.03 0.2 0.3 True
ZALANDO BPR-MAX ELU-0.5 0.1 0.3 0.1 False
DIGINETICA TOP1-MAX Linear 0.05 0.0 0.4 True
DIGINETICA (STAMP) TOP1-MAX ELU-0.5 0.07 0.0 0.6 True
8TRACKS TOP1-MAX ELU-0.5 0.04 0.3 0.8 True
AOTM TOP1-MAX ELU-0.5 0.04 0.6 0.0 False
NOWPLAYING TOP1-MAX ELU-0.5 0.05 0.1 0.6 True
30MUSIC TOP1-MAX ELU-0.5 0.05 0.1 0.6 True

Hyperparameters for stamp (fixed layer size of 100)

We tested the following hyperparameter space:

Parameter From To Steps
Number of Epochs 10 30 10
Decay Rate 0.0 0.9 10
Initial Learning Rate 0.001
0.0001		 0.01
0.001		 10
10

Dataset Number of Epochs Decay Rate Initial Learning Rate
RSC15 20 0 0.0007
RETAILROCKET 10 0.6 0.0008
ZALANDO 30 0.7 0.009
DIGINETICA 20 0.1 0.0009
DIGINETICA (STAMP) 20 0.1 0.0008
8TRACKS 30 0.0 0.0008
AOTM 30 0 0.004
NOWPLAYING 20 0.9 0.0005
30MUSIC 10 0.4 0.003

Hyperparameters for narm (fixed factors' number of 100, layer size of of 100, and epochs' number of 20)

We tested the following hyperparameter space:

Parameter From To Steps
Learning Rate 0.1
0.5		 0.01
0.1		 10
5

Dataset Learning Rate
RSC15 0.0008
RETAILROCKET 0.01
ZALANDO 0.007
DIGINETICA 0.0007
DIGINETICA (STAMP) 0.008
8TRACKS 0.002
AOTM 0.004
NOWPLAYING 0.004
30MUSIC 0.007

Hyperparameters for nextitnet (?)

We tested the following hyperparameter space:

Parameter From To Steps
Learning Rate 0.01
0.001		 0.001
0.0001		 10
5
Iterations 10 30 10
Negative Sampling True False -

Dataset Learning Rate Iterations Negative Sampling
RETAILROCKET 0.006 10 True
DIGINETICA 0.003 10 False
DIGINETICA (STAMP) 0.009 20 False
AOTM 0.005 30 True

Hyperparameters for ar
fixed pruning size of 20

Hyperparameters for sr (fixed pruning size of 100)

We tested the following hyperparameter space:

Parameter From To Steps Options
Steps 1 20 1 -
Weighting - - - Div, Linear, Quadratic, Log, Same

Dataset Steps Weighting
RSC15 8 Div
RETAILROCKET 7 Div
ZALANDO 3 Quadratic
DIGINETICA 25 Div
DIGINETICA (STAMP) 30 Quadratic
8TRACKS 25 Log
AOTM 6 Div
NOWPLAYING 9 Quadratic
30MUSIC 30 Quadratic

Hyperparameters for sknn (fixed sampling mode of recent)

We tested the following hyperparameter space:

Parameter Options
Number of Neighbors 50, 100, 500, 1000, 1500
Sample Size 500, 1000, 2500, 5000, 10000
Similarity Cosine, Jaccard

Dataset Number of Neighbors Sample Size Similarity
RSC15 500 10000 Jaccard
RETAILROCKET 50 5000 Cosine
ZALANDO 50 10000 Cosine
DIGINETICA 100 500 Cosine
DIGINETICA (STAMP) 1000 5000 Cosine
8TRACKS 1000 1000 Cosine
AOTM 50 1000 Cosine
NOWPLAYING 50 2500 Jaccard
30MUSIC 100 500 Cosine

Hyperparameters for vsknn (fixed sampling mode of recent)

We tested the following hyperparameter space:

Parameter Options
Number of Neighbors 50, 100, 500, 1000, 1500
Sample Size 500, 1000, 2500, 5000, 10000
Weighting Same, Div, Linear, Quadratic, Log
Weighting Score Same, Div, Linear, Quadratic, Log
IDF Weighting False, 1, 2, 5, 10

Dataset Number of Neighbors Sample Size Weighting Weighting Score IDF_Weighting
RSC15 100 1000 Quadratic Quadratic False
RETAILROCKET 1500 2500 Same Linear 10
ZALANDO 50 10000 Log Quadratic 10
DIGINETICA 500 5000 Quadratic Div 5
DIGINETICA (STAMP) 50 2500 Log Quadratic 1
8TRACKS 100 5000 Quaratic Quadratic False
AOTM 50 100 Div Quadratic False
NOWPLAYING 100 2500 Quadratic Quadratic False
30MUSIC 100 10000 Quadratic Quadratic False

Hyperparameters for vsknn

We tested the following hyperparameter space:

Parameter Options
Expert StdExpert, DirichletExpert
Max Considered Context Length 5,10,20,30,40,50,75
Number of Recent Candidates (Only for Adaptive Configuration) 5,10,20,30,40,50,75

Dataset Expert Max Considered Context Length Number of Recent Candidates
All StdExpert 50 1000

Hyperparameters for sgnn (fixed layer size of 100)

We tested the following hyperparameter space:

Parameter From To Steps
Learning Rate 0.01
0.001		 0.001
0.0001		 10
10
L2 Penalty 0.0001
0.00001		 0.00001
0.000001		 10
10
Decay Rate 0.1 0.9 10
Decay Rate Step 3 7 2

Dataset Learning Rate L2 Penalty Decay Rate Decay Rate Step
RSC15
RETAILROCKET 0.0002 0.000003 0.54 3
ZALANDO
DIGINETICA 0.0001 0.00001 0.1 5
DIGINETICA (STAMP)
8TRACKS
AOTM 0.001 0.00006 0.1 7
NOWPLAYING 0.006 0.000007 0.1 3
30MUSIC