diff options
Diffstat (limited to 'worker.py')
| -rw-r--r-- | worker.py | 24 |
1 files changed, 12 insertions, 12 deletions
@@ -27,7 +27,7 @@ mvpmodel = None def connect(): - global Match, Roster, Participant, ParticipantStats, Player + global Match, Roster, Participant, Hero, ParticipantStats, Player global db # generate schema from db @@ -58,6 +58,7 @@ def connect(): Participant.hero = relationship( "hero", foreign_keys="hero.id", primaryjoin="and_(hero.id == participant.hero_id)") + Hero = Base.classes.hero ParticipantStats = Base.classes.participant_stats Participant.participant_stats = relationship( "participant_stats", foreign_keys="participant_stats.participant_api_id", @@ -106,15 +107,17 @@ class Model(object): if ids is None: # training, get random sample size = size or self.batchsize # train a model one batch - offset = random.random() * self._db.query(Participant).count() + offset = random.random() * self._db.query(Participant)\ + .count() # have a bit of randomness in the sample - records = self._db.query( - Participant).offset(offset).limit(size).all() + records = self._db.query(Participant)\ + .offset(offset).limit(size)\ + .all() else: - records = self._db.query( - Participant).filter( - Participant.api_id.in_(ids)).order_by( - Participant.api_id.desc()).all() + records = self._db.query(Participant)\ + .filter(Participant.api_id.in_(ids))\ + .order_by(Participant.api_id.desc())\ + .all() data = {} labels = [] @@ -162,10 +165,7 @@ class Model(object): class MVPScoreModel(Model): def __init__(self, db): - self.features = ["participant_stats.kills", - "participant_stats.deaths", - "participant_stats.assists", - "roster.hero_kills"] + self.features = ["participant_stats.non_jungle_minion_kills"] self.label = "participant_stats.impact_score" self.type = "linear" self.batches = 1 |