Created
May 15, 2019 03:27
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| # train a model, but first, pull everything to the driver node | |
| df = spark_df.toPandas().drop(['user_id', 'partition_id'], axis = 1) | |
| y_train = df['label'] | |
| x_train = df.drop(['label'], axis=1) | |
| # use logistic regression | |
| model = LogisticRegression() | |
| model.fit(x_train, y_train) |
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