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Update examples
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12 files changed

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-311
lines changed

‎examples/fraud/implementations/models/dnn.py‎

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@@ -11,5 +11,6 @@ def create_estimator(run_config, model_config):
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feature_columns=feature_columns,
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hidden_units=model_config["hparams"]["hidden_units"],
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n_classes=2,
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weight_column="class_weight",
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config=run_config,
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)

‎examples/fraud/implementations/models/dnn_weighted.py‎

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‎examples/fraud/implementations/transformers/weight.py‎

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@@ -5,5 +5,5 @@ def transform_spark(data, columns, args, transformed_column):
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return data.withColumn(
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transformed_column,
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F.when(data[columns["col"]] == 0, 1 - distribution[0]).otherwise(1 - distribution[1]),
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F.when(data[columns["col"]] == 0, distribution[1]).otherwise(distribution[0]),
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)

‎examples/fraud/resources/apis.yaml‎

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- kind: api
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name: fraud
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model_name: dnn_weighted
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model_name: dnn
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compute:
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replicas: 1

‎examples/fraud/resources/environments.yaml‎

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path: s3a://cortex-examples/fraud.csv
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csv_config:
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header: true
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schema:
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- time
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- v1
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- v2
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- v3
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- v4
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- v5
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- v6
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- v7
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- v8
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- v9
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- v10
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- v11
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- v12
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- v13
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- v14
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- v15
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- v16
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- v17
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- v18
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- v19
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- v20
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- v21
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- v22
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- v23
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- v24
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- v25
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- v26
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- v27
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- v28
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- amount
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- class
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schema: [time, v1, v2, v3, v4, v5, v6, v7, v8, v9, v10, v11, v12, v13, v14, v15, v16, v17, v18, v19, v20, v21, v22, v23, v24, v25, v26, v27, v28, amount, class]
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- kind: raw_column
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name: time
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v1
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v2
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v3
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v4
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v5
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v6
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v7
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v8
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v9
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v10
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v11
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v12
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v13
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v14
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v15
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v16
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v17
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v18
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v19
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v20
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v21
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v22
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v23
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v24
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v25
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v26
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v27
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: v28
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: amount
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type: FLOAT_COLUMN
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required: true
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- kind: raw_column
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name: class
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type: INT_COLUMN
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required: true

‎examples/fraud/resources/models.yaml‎

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- kind: model
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name: dnn_weighted
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type: classification
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target_column: class
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feature_columns:
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- time_normalized
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- v1_normalized
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- v2_normalized
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- v3_normalized
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- v4_normalized
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- v5_normalized
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- v6_normalized
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- v7_normalized
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- v8_normalized
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- v9_normalized
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- v10_normalized
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- v11_normalized
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- v12_normalized
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- v13_normalized
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- v14_normalized
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- v15_normalized
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- v16_normalized
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- v17_normalized
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- v18_normalized
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- v19_normalized
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- v20_normalized
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- v21_normalized
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- v22_normalized
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- v23_normalized
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- v24_normalized
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- v25_normalized
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- v26_normalized
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- v27_normalized
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- v28_normalized
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- amount_normalized
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training_columns:
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- class_weight
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hparams:
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hidden_units: [100, 100, 100]
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data_partition_ratio:
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training: 0.8
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evaluation: 0.2
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training:
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num_steps: 5000
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- kind: model
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name: dnn
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type: classification
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target_column: class
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feature_columns:
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- time_normalized
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- v1_normalized
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- v2_normalized
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- v3_normalized
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- v4_normalized
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- v5_normalized
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- v6_normalized
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- v7_normalized
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- v8_normalized
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- v9_normalized
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- v10_normalized
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- v11_normalized
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- v12_normalized
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- v13_normalized
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- v14_normalized
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- v15_normalized
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- v16_normalized
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- v17_normalized
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- v18_normalized
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- v19_normalized
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- v20_normalized
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- v21_normalized
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- v22_normalized
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- v23_normalized
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- v24_normalized
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- v25_normalized
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- v26_normalized
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- v27_normalized
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- v28_normalized
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- amount_normalized
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[time_normalized, v1_normalized, v2_normalized, v3_normalized, v4_normalized,
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v5_normalized, v6_normalized, v7_normalized, v8_normalized, v9_normalized,
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v10_normalized, v11_normalized, v12_normalized, v13_normalized, v14_normalized,
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v15_normalized, v16_normalized, v17_normalized, v18_normalized, v19_normalized,
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v20_normalized, v21_normalized, v22_normalized, v23_normalized, v24_normalized,
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v25_normalized, v26_normalized, v27_normalized, v28_normalized, amount_normalized]
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training_columns: [class_weight]
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hparams:
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hidden_units: [100, 100, 100]
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data_partition_ratio:

‎examples/fraud/resources/templates.yaml‎ renamed to ‎examples/fraud/resources/normalize.yaml‎

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- kind: transformed_column
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name: {column}_normalized
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tags:
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type: numeric
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transformer: cortex.normalize
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inputs:
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columns:

‎examples/fraud/resources/features.yaml‎ renamed to ‎examples/fraud/resources/normalized_columns.yaml‎

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template: normalize
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args:
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column: amount
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- kind: aggregate
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name: class_distribution
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aggregator: cortex.class_distribution_int
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inputs:
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columns:
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col: class
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- kind: transformed_column
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name: class_weight
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transformer: weight
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inputs:
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columns:
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col: class
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args:
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class_distribution: class_distribution

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