Row 94614
Content Data
This page contains data entry 94614 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.
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.
| Field | Value |
|---|---|
| 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 |
| username_encoded | Z0FBQUFBQm5Lak10dmllSVpmY3p6dHEzY0E4enlOazd0LUVmd2VXMnNtMGdRTS01Y2dTZjhtbDFDT2JnYXlZN1lCVmIzN25lRHg3c1VBWVVjU1lrUmh2QVBndnFQSnJ6UUE9PQ== |
| url_encoded | Z0FBQUFBQm5Lak9feFZlVm5PbDd5b1pFM3RpVHk5S0J6NVhrZWZQZUFEY1JsNTU1c1hCalNnZmgycWVLUk16bDFOY0tVSUpLMUVvcHJZS3JBblV5WGZkSlZjQURpMFg5RE1IblRQTDg2Zm5hTllMXzlJMlgzOXpKeGppek8xZEZZYmhiUzVaYmNUcEMxcDNydzJ4bWc5WGhNbEU3SW51OC01RS1fVnRLMFNLQTE4UF82Z183ZS1ZTEFDUG1WeDhMVjhXQUxiQlJTUTJtMnJYaFcwUkZjMzFuSHBMZEF6X3FWVTFlc0Z3VWhNQTF2MUxUY0VMbFB2TT0= |
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==",
"url_encoded": "Z0FBQUFBQm5Lak9feFZlVm5PbDd5b1pFM3RpVHk5S0J6NVhrZWZQZUFEY1JsNTU1c1hCalNnZmgycWVLUk16bDFOY0tVSUpLMUVvcHJZS3JBblV5WGZkSlZjQURpMFg5RE1IblRQTDg2Zm5hTllMXzlJMlgzOXpKeGppek8xZEZZYmhiUzVaYmNUcEMxcDNydzJ4bWc5WGhNbEU3SW51OC01RS1fVnRLMFNLQTE4UF82Z183ZS1ZTEFDUG1WeDhMVjhXQUxiQlJTUTJtMnJYaFcwUkZjMzFuSHBMZEF6X3FWVTFlc0Z3VWhNQTF2MUxUY0VMbFB2TT0="
}
Entry Information
- Entry ID: 94614
- Repository: Axioma AXP
- Dataset: arrmlet/reddit_dataset_36
- Total Entries: 100,000