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| author | schneefux <schneefux+commit@schneefux.xyz> | 2017-05-28 13:04:42 +0200 |
|---|---|---|
| committer | schneefux <schneefux+commit@schneefux.xyz> | 2017-05-28 13:04:42 +0200 |
| commit | e2f8ff5759665d24321bebd729fcf1fda0f844a3 (patch) | |
| tree | 12170c5991ad47750a28c16cfb29fced0fad0a69 | |
| parent | b0020a373ce82332756329f98b8912d949b852fa (diff) | |
| download | analyzer-e2f8ff5759665d24321bebd729fcf1fda0f844a3.tar.gz analyzer-e2f8ff5759665d24321bebd729fcf1fda0f844a3.zip | |
code for new role scores
| -rw-r--r-- | rolerate.py | 23 |
1 files changed, 15 insertions, 8 deletions
diff --git a/rolerate.py b/rolerate.py index 7d1e0ef..42ef8a5 100644 --- a/rolerate.py +++ b/rolerate.py @@ -70,7 +70,7 @@ def connect(): class RoleModel(object): def __init__(self, db): - self.batches = 10 + self.batches = 3 self.batchsize = 300 self.testsize = 1000 self.steps = 300 @@ -78,8 +78,10 @@ class RoleModel(object): self._db = db self._feature_cols = [ - tf.contrib.layers.real_valued_column("lane_cs", dimension=1), - tf.contrib.layers.real_valued_column("jungle_cs", dimension=1) + tf.contrib.layers.real_valued_column("farm", dimension=1), + tf.contrib.layers.real_valued_column("kills", dimension=1), + tf.contrib.layers.real_valued_column("deaths", dimension=1), + tf.contrib.layers.real_valued_column("assists", dimension=1) ] self._model = tf.contrib.learn.LinearClassifier( feature_columns=self._feature_cols, @@ -100,12 +102,17 @@ class RoleModel(object): data = {} labels = [] # populate from db records - data["lane_cs"] = [] - data["jungle_cs"] = [] + data["farm"] = [] + data["kills"] = [] + data["deaths"] = [] + data["assists"] = [] for record in records: - labels.append(record.hero[0].is_jungler) - data["lane_cs"].append(record.participant_stats[0].non_jungle_minion_kills) - data["jungle_cs"].append(record.participant_stats[0].jungle_kills) + if (record.hero[0].is_jungler): + labels.append(record.winner) + data["farm"].append(record.participant_stats[0].farm) + data["kills"].append(record.participant_stats[0].kills) + data["deaths"].append(record.participant_stats[0].deaths) + data["assists"].append(record.participant_stats[0].assists) logging.info("---------- %s data points for training ---------", len(labels)) # convert to numpy arrs |