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config.py
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config.py
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################### Select Models ##################
models = [
#['basicFM','FM','Basic',['2']],
#['bmt','FM','BasicMovieTag',['2']],
#['amt','FM','AdjustedMovieTag',['2']]
#['nn', 'FM', 'NearestNeighbor',['2']]
#['rmt','FM','RelatedMovieTag',['2']]
#['basicSVD','SVD','Basic',[]]
['ImplicitFeedbackSVD','SVD','ImplicitFeedback',[]]
]
# Defining models:
# Each element is a list:
# [tag,program,setting,misc]
# tag is the name of the model
# program specifies which program to use
# setting defines which features will be used
# Misc depends on the program:
# For FM: [dims]
# For SVDFeature: []
ensembleModels = [ ['OLSR','OLS',[]],
# ['OLSI','OLSI',['2']],
# ['RR' ,'RR',['2']],
# ['BRT','BRT',[]],
# ['BMAR','BMAR',[]],
# ['RFR' ,'RFR' ,[]],
# ['CIRF','CIRF',[]], Not Working
['Lasso','Lasso',[]],
['GBRT','GBRT',['50']]
]
# Defining ensamble models:
# Each element is a list:
# [tag,modelType,misc]
# tag is the name of the model
# modelType defines what model to use
# misc is the arguments to the program
synthModel = ['OLSR','OLS',[]]
################### Select Parts ##################
LAPTOP_TEST = True # uses small data set to run features on laptop
TRIALS = 2
PRE_PROCESS = True
DE_EFFECT = False #If De-effect is false, model predictions are correct
SETUP_MODELS = True
RUN_MODELS = True
SETUP_HYBRID = False
RUN_HYBRID = False
SETUP_SYNTHESIZE = False
RUN_SYNTHESIZE = False
POST_PROCESS = False
################## Select Bootstrap Parameters ##################
BOOTSTRAP_SPLITS = [.8,.8]
################## Timer ##############
TIME_RUN = False
################## Factorization Machines ##########
FM_ITER = 2
FM_STR_ITER = str(FM_ITER)
FM_INIT_STD = '.3'
################## SVD Feature #####################
SVD_LEARNING_RATE = '.005'
SVD_REGULARIZATION_ITEM = '.004'
SVD_REGULARIZATION_USER = '.004'
SVD_REGULARIZATION_GLOBAL = '.001'
SVD_REGULARIZATION_FEEDBACK = '.004'
SVD_NUM_FACTOR = '64'
SVD_ACTIVE_TYPE = '0'
SVD_NUM_ITER = '10'
################## Hybrid #########################