Python SommelierYeungMFRecommender Examples

Example #1

#!flask/bin/python
from src.recommender import SommelierYeungMFRecommender, SommelierRecommender
y = SommelierYeungMFRecommender()
y.split_data_evaluation([
    {"steps":1000,  "factors":10, "verbose":False},
], percent_train=95)
y.split_data_evaluation([
    {"steps":1000,  "factors":10, "verbose":False},
], percent_train=90)
y.split_data_evaluation([
    {"steps":1000,  "factors":10, "verbose":False},
], percent_train=85)

"""
Test/train split: 90/10
Evaluation for args: {'steps': 50, 'verbose': False, 'factors': 8}
NMAE 0.184606174037
MAE 0.923030870186
Total SD 0.74469464146
Author SDs {1: 0.66691197956843939, 2: 0.0, 3: 0.50279609651399249, 4: 0.57237094012612644, 5: 0.0, 10: 0.93620342958216529, 11: 0.57349908937180116, 12: 0.0, 13: 0.0, 14: 0.8401937215050671, 15: 0.19693957208969942, 16: 0.7473842558426278, 19: 0.79671806235540932}
Evaluation for args: {'steps': 50, 'verbose': False, 'factors': 8}
NMAE 0.177914688924
MAE 0.889573444621
Total SD 0.652182399073
Author SDs {1: 0.62928766408505432, 2: 0.0, 3: 0.59126553483873812, 4: 0.81513353713631542, 5: 0.0, 10: 0.07060409201739537, 11: 0.68872807551849069, 12: 0.0, 13: 0.0, 14: 0.62832339743318222, 15: 0.25462026420405665, 16: 0.41593979883552951, 19: 0.72265255016617702}
Evaluation for args: {'steps': 50, 'verbose': False, 'factors': 8}
NMAE 0.170369383859
MAE 0.851846919296
Total SD 0.718613078166
Author SDs {1: 0.59549749661482498, 2: 0.0, 3: 0.53760952462379241, 4: 0.65434050587508441, 5: 0.0, 10: 1.0949595865167969, 11: 0.65149354023737527, 12: 0.0, 13: 0.0, 14: 0.86791595910838881, 15: 0.30065848818498891, 16: 0.79978085141610344, 19: 0.31049227438073551}
Evaluation for args: {'steps': 50, 'verbose': False, 'factors': 8}

Example #2

File: eval_train_movielens.py Project: pgchamberlin/sommelier

#!flask/bin/python
from src.recommender import SommelierYeungMFRecommender, SommelierRecommender
y = SommelierYeungMFRecommender()
y.split_data_evaluate_movielens_file('ml-100k/u.data', [
    {"steps":1,  "factors":10, "verbose":True},
    {"steps":2,  "factors":10, "verbose":True},
    {"steps":3,  "factors":10, "verbose":True},
    {"steps":4,  "factors":10, "verbose":True},
    {"steps":5,  "factors":10, "verbose":True},
    {"steps":6,  "factors":10, "verbose":True},
    {"steps":7,  "factors":10, "verbose":True},
    {"steps":8,  "factors":10, "verbose":True},
    {"steps":9,  "factors":10, "verbose":True},
    {"steps":10,  "factors":10, "verbose":True},
    {"steps":12,  "factors":10, "verbose":True},
    {"steps":14,  "factors":10, "verbose":True},
    {"steps":16,  "factors":10, "verbose":True},
], percent_train=80)

y.split_data_evaluate_movielens_file('ml-100k/u.data', [
    {"steps":1,  "factors":10, "verbose":True},
    {"steps":2,  "factors":10, "verbose":True},
    {"steps":3,  "factors":10, "verbose":True},
    {"steps":4,  "factors":10, "verbose":True},
    {"steps":5,  "factors":10, "verbose":True},
    {"steps":6,  "factors":10, "verbose":True},
    {"steps":7,  "factors":10, "verbose":True},
    {"steps":8,  "factors":10, "verbose":True},
    {"steps":9,  "factors":10, "verbose":True},
    {"steps":10,  "factors":10, "verbose":True},
    {"steps":12,  "factors":10, "verbose":True},

Example #3

File: yeung_mf_evaluation.py Project: GuoYunZheSE/sommelier

#!flask/bin/python
from src.recommender import SommelierYeungMFRecommender, SommelierRecommender
y = SommelierYeungMFRecommender()
m = y.generate_lists_ui_matrix()
y.multiple_factorizations(m, [
    {
        "steps": 3500,
        "factors": 15
    },
    {
        "steps": 4000,
        "factors": 15
    },
])
y.multiple_factorizations(m, [
    {
        "steps": 3500,
        "factors": 20
    },
    {
        "steps": 4000,
        "factors": 20
    },
])

Example #4

#!flask/bin/python
from src.recommender import SommelierYeungMFRecommender, SommelierRecommender

y = SommelierYeungMFRecommender()
y.split_data_evaluate_movielens_file('ml-100k/u.data', [
    {
        "steps": 1,
        "factors": 10,
        "verbose": True
    },
    {
        "steps": 2,
        "factors": 10,
        "verbose": True
    },
    {
        "steps": 3,
        "factors": 10,
        "verbose": True
    },
    {
        "steps": 4,
        "factors": 10,
        "verbose": True
    },
    {
        "steps": 5,
        "factors": 10,
        "verbose": True
    },
    {