Row 50157

Row ID: 50157 | Dataset Entry | Axioma AXP Content Repository

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I believe this wouldn't work, because depending on the noise the image might indeed be a little closer to some digits than the others. If you assign equal probability to all digits for all noisy images, that would (ironically) introduce a lot of noise. Maybe I am wrong, but I don't think this would help model with positive examples at all (examples where there is indeed a digit in the image).

FieldValue
text I believe this wouldn't work, because depending on the noise the image might indeed be a little closer to some digits than the others. If you assign equal probability to all digits for all noisy images, that would (ironically) introduce a lot of noise. Maybe I am wrong, but I don't think this would help model with positive examples at all (examples where there is indeed a digit in the image).
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-22
username_encoded Z0FBQUFBQm5Lak1TN0J4MzhFLVljRlVZVjFQQkNpTjQyODNQcVowVU9CODIzZ2dUcUYtMFVWcHJSUW9GYzZJa1hUWnFDN0YxTjZwRUpzRUNCUjVtZHlSNUYzNUNfa0Z2dlE9PQ==
url_encoded Z0FBQUFBQm5Lak9pRU9RQ3Q4bWUyVVl1clF1QXFsR0thWGtiOWMySHkzaGVGN2RkY3lSRVpYWFlfcjE3eTk2N1FvWG54UVNpdTVVUm1Pb2kzejBnQ3dZU3FzVjBjSDZYMnJGRkNZR3RsVDNRWlV0ZFV0N2dTb0xOZ1Z0bUlrcWRHd3hiWGlFbUdtc1VfZFV2TkJpREs0MmJjTi1ucUlGOHNHVEliU0pEZ2lQMS1xbWo2MWhRMWExZnhjanRKYlBvbmZHT3pRWFRYa0V4V1RnbEJrSlhkOXZWSTVYMXgyVkZRZz09

Raw Record

{
  "text": "I believe this wouldn't work, because depending on the noise the image might indeed be a little closer to some digits than the others. If you assign equal probability to all digits for all noisy images, that would (ironically) introduce a lot of noise. Maybe I am wrong, but I don't think this would help model with positive examples at all (examples where there is indeed a digit in the image).",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-22",
  "username_encoded": "Z0FBQUFBQm5Lak1TN0J4MzhFLVljRlVZVjFQQkNpTjQyODNQcVowVU9CODIzZ2dUcUYtMFVWcHJSUW9GYzZJa1hUWnFDN0YxTjZwRUpzRUNCUjVtZHlSNUYzNUNfa0Z2dlE9PQ==",
  "url_encoded": "Z0FBQUFBQm5Lak9pRU9RQ3Q4bWUyVVl1clF1QXFsR0thWGtiOWMySHkzaGVGN2RkY3lSRVpYWFlfcjE3eTk2N1FvWG54UVNpdTVVUm1Pb2kzejBnQ3dZU3FzVjBjSDZYMnJGRkNZR3RsVDNRWlV0ZFV0N2dTb0xOZ1Z0bUlrcWRHd3hiWGlFbUdtc1VfZFV2TkJpREs0MmJjTi1ucUlGOHNHVEliU0pEZ2lQMS1xbWo2MWhRMWExZnhjanRKYlBvbmZHT3pRWFRYa0V4V1RnbEJrSlhkOXZWSTVYMXgyVkZRZz09"
}
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