Row 94614

Row ID: 94614 | Dataset Entry | Axioma AXP Content Repository

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I didn't mean fitting the knn, I meant fitting the scaler. When you scaler.fit\_transform the whole data before the cross validation, instead of scaler.fit\_transform the train and scaler.transform the test/validation at every fold, that is data leakage as you leak test/validation distribution into the scaling equation (That is you are scaling the train data also using the test/validation values).

Different min-max values in the test/validation will change the scaling of the values, changing how much that feature contributes to the distance.

FieldValue
text I didn't mean fitting the knn, I meant fitting the scaler. When you scaler.fit\_transform the whole data before the cross validation, instead of scaler.fit\_transform the train and scaler.transform the test/validation at every fold, that is data leakage as you leak test/validation distribution into the scaling equation (That is you are scaling the train data also using the test/validation values). Different min-max values in the test/validation will change the scaling of the values, changing h…
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-25
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Raw Record

{
  "text": "I didn't mean fitting the knn, I meant fitting the scaler. When you scaler.fit\\_transform the whole data before the cross validation, instead of scaler.fit\\_transform the train and scaler.transform the test/validation at every fold, that is data leakage as you leak test/validation distribution into the scaling equation (That is you are scaling the train data also using the test/validation values). \n\nDifferent min-max values in the test/validation will change the scaling of the values, changing how much that feature contributes to the distance.",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-25",
  "username_encoded": "Z0FBQUFBQm5Lak10dmllSVpmY3p6dHEzY0E4enlOazd0LUVmd2VXMnNtMGdRTS01Y2dTZjhtbDFDT2JnYXlZN1lCVmIzN25lRHg3c1VBWVVjU1lrUmh2QVBndnFQSnJ6UUE9PQ==",
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Entry Information