Row 5243

Row ID: 5243 | Dataset Entry | Axioma AXP Content Repository

Content Data

This page contains data entry 5243 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

Hey everyone,

I’m relatively new to data science and currently working on a project that involves a dataset with over 60 columns. Many of these columns are categorical, with more than 100 unique values each.

My issue arises when I try to apply one-hot encoding to these categorical columns. It seems like I’m running into the curse of dimensionality problem, and I’m not quite sure how to proceed from here.

I’d really appreciate some advice or guidance on how to effectively handle high-dimensional data in this context. Are there alternative encoding techniques I should consider? Or perhaps there are preprocessing steps I’m overlooking?

Any insights or tips would be immensely helpful.

Thanks in advance!

FieldValue
text Hey everyone, I’m relatively new to data science and currently working on a project that involves a dataset with over 60 columns. Many of these columns are categorical, with more than 100 unique values each. My issue arises when I try to apply one-hot encoding to these categorical columns. It seems like I’m running into the curse of dimensionality problem, and I’m not quite sure how to proceed from here. I’d really appreciate some advice or guidance on how to effectively handle high-dimension…
label r/datascience
dataType post
communityName r/datascience
datetime 2024-04-28
username_encoded Z0FBQUFBQm5Lakwyc0hFRE96XzRqcVZFc3Z6UGxCR0xlZFRLdzl3aVdNT3pYcFVzR2Zadm1UVUtjTFA5bVlOOGEtWi1VNEhDSWc3ajU1ajV2dEI2NFpUNVZmNXQ0MUZIa2NqZ3laTkdWNDA4bmVfdjdiQ1dXNTQ9
url_encoded Z0FBQUFBQm5Lak9Gd1FnOFhKT3VBWFc0UzMwbkhwMkRPNE0tUTBwbDhqY3laNmRsUUtHekU0UnVScFBIbURucWhNdlZ6Y2tpMjY1NHAxbC1idDR1UDJFU3E5MnMzVWdqMjUzeUN6ZV9TaUdkUkctUUEtcGM2eGYtOUJQOEszVk96VmNkZldXeTA2LU1GdFZaWjBlem1oYjN4Vm1oQWVBbU5KN0tGMmZZLW1vc0xEZFhJUWRUUUZ3cV8yZzlWRzZvWnNIYWNhM054TDA0c21NcFpNUnBESlpjUzZYaENURjFXQT09

Raw Record

{
  "text": "Hey everyone,\n\nI’m relatively new to data science and currently working on a project that involves a dataset with over 60 columns. Many of these columns are categorical, with more than 100 unique values each.\n\nMy issue arises when I try to apply one-hot encoding to these categorical columns. It seems like I’m running into the curse of dimensionality problem, and I’m not quite sure how to proceed from here.\n\nI’d really appreciate some advice or guidance on how to effectively handle high-dimensional data in this context. Are there alternative encoding techniques I should consider? Or perhaps there are preprocessing steps I’m overlooking?\n\nAny insights or tips would be immensely helpful. \n\nThanks in advance!",
  "label": "r/datascience",
  "dataType": "post",
  "communityName": "r/datascience",
  "datetime": "2024-04-28",
  "username_encoded": "Z0FBQUFBQm5Lakwyc0hFRE96XzRqcVZFc3Z6UGxCR0xlZFRLdzl3aVdNT3pYcFVzR2Zadm1UVUtjTFA5bVlOOGEtWi1VNEhDSWc3ajU1ajV2dEI2NFpUNVZmNXQ0MUZIa2NqZ3laTkdWNDA4bmVfdjdiQ1dXNTQ9",
  "url_encoded": "Z0FBQUFBQm5Lak9Gd1FnOFhKT3VBWFc0UzMwbkhwMkRPNE0tUTBwbDhqY3laNmRsUUtHekU0UnVScFBIbURucWhNdlZ6Y2tpMjY1NHAxbC1idDR1UDJFU3E5MnMzVWdqMjUzeUN6ZV9TaUdkUkctUUEtcGM2eGYtOUJQOEszVk96VmNkZldXeTA2LU1GdFZaWjBlem1oYjN4Vm1oQWVBbU5KN0tGMmZZLW1vc0xEZFhJUWRUUUZ3cV8yZzlWRzZvWnNIYWNhM054TDA0c21NcFpNUnBESlpjUzZYaENURjFXQT09"
}
Explore Dataset Explore Row

Entry Information