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@vivek081166 vivek081166/h2o_automl.py
Last active Apr 23, 2019

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import h2o
from h2o.automl import H2OAutoML
h2o.init()
# サンプルバイナリ結果トレイン/テストセットをH2Oにインポートする
train = h2o.import_file("https://s3.amazonaws.com/erin-data/higgs/higgs_train_10k.csv")
test = h2o.import_file("https://s3.amazonaws.com/erin-data/higgs/higgs_test_5k.csv")
# 予測子とレスポンスを特定する
x = train.columns
y = "response"
x.remove(y)
# 二項分類の場合
train[y] = train[y].asfactor()
test[y] = test[y].asfactor()
# AutoMLを30秒間実行する
aml = H2OAutoML(max_runtime_secs = 30)
aml.train(x = x, y = y,
training_frame = train,
leaderboard_frame = test)
# AutoMLリーダーボードを見る
lb = aml.leaderboard
lb
# model_id auc logloss
# -------------------------------------------------- -------- ---------
# StackedEnsemble_model_1494643945817_1709 0.780384 0.561501
# GBM_grid__95ebce3d26cd9d3997a3149454984550_model_0 0.764791 0.664823
# GBM_grid__95ebce3d26cd9d3997a3149454984550_model_2 0.758109 0.593887
# DRF_model_1494643945817_3 0.736786 0.614430
# XRT_model_1494643945817_461 0.735946 0.602142
# GBM_grid__95ebce3d26cd9d3997a3149454984550_model_3 0.729492 0.667036
# GBM_grid__95ebce3d26cd9d3997a3149454984550_model_1 0.727456 0.675624
# GLM_grid__95ebce3d26cd9d3997a3149454984550_model_1 0.685216 0.635137
# GLM_grid__95ebce3d26cd9d3997a3149454984550_model_0 0.685216 0.635137
# リーダーモデルはここに保存されています
aml.leader
# 予測
# 方法 1
preds = aml.predict(test)
# または方法 2
preds = aml.leader.predict(test)
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