Row 7888

Row ID: 7888 | Dataset Entry | Axioma AXP Content Repository

Content Data

This page contains data entry 7888 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

A common trend for model evaluation that we often see is the use of Cross validation CV. Authors often report accuracy and other metrics (f-measure, precision,..etc) derived from this approach. Alongside that, they plot training and validation graphs for both loss and accuracy as well as confusion matrices. My question is about how these graphs are generated. Are they plotted using the k folds of cross-validation, or is there another method at play ? An example is in the paper in the link below : [link to example](https://www.researchgate.net/publication/367565701_An_Adaptive_Batch_Size_based-CNN-LSTM_Framework_for_Human_Activity_Recognition_in_Uncontrolled_Environment)

FieldValue
text A common trend for model evaluation that we often see is the use of Cross validation CV. Authors often report accuracy and other metrics (f-measure, precision,..etc) derived from this approach. Alongside that, they plot training and validation graphs for both loss and accuracy as well as confusion matrices. My question is about how these graphs are generated. Are they plotted using the k folds of cross-validation, or is there another method at play ? An example is in the paper in the link belo…
label r/machinelearning
dataType post
communityName r/MachineLearning
datetime 2024-05-18
username_encoded Z0FBQUFBQm5LakwzZ1JaUWRyRGUydzdIWlBSaFFxQUVWU3A2dGN1Wkx0T09aYVNkS2lPSkR2OVB4QkFPZFFjVVJ2Yl9NdlNoODhLbkJOSWxmcVo0YmNDNDdtVVBiQm12TGc9PQ==
url_encoded Z0FBQUFBQm5Lak9ISFhVTkRjYk5DSUs3Szk2SGFLX25lMDFYd1Itbm9saFRnMVg4X214b055VHFOTjBKUTZ3RXJOcURFbVNEdXZjaWR2V3d5VFpMTUpvek9lajJEMlRuaDRmcl8zTkJEZGF3ZjVwSlduMWkwQnA1NWRXcldPVHIwaW1rcm9YQU9Fd3NaUkFSYUZpMnp1Q3E3STNReTNCMThqMDBGaW1Kb2ltMWdmSDlZcW1VZUJ1bmZ2cXdXbmIzTVhYcmIyNkx5ZzI3RDBhZGVPTF8zZE5DZE1lVFZHdWFNZz09

Raw Record

{
  "text": "A common trend for model evaluation that we often see is the use of Cross validation CV. Authors  often report accuracy and other metrics (f-measure, precision,..etc) derived from this approach. Alongside that, they plot training and validation graphs for both loss and accuracy as well as confusion matrices. My question is about how these graphs are generated. Are they plotted using the k folds of cross-validation, or is there another method at play ?  An example is in the paper in the link below :   [link to example](https://www.researchgate.net/publication/367565701_An_Adaptive_Batch_Size_based-CNN-LSTM_Framework_for_Human_Activity_Recognition_in_Uncontrolled_Environment)",
  "label": "r/machinelearning",
  "dataType": "post",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-18",
  "username_encoded": "Z0FBQUFBQm5LakwzZ1JaUWRyRGUydzdIWlBSaFFxQUVWU3A2dGN1Wkx0T09aYVNkS2lPSkR2OVB4QkFPZFFjVVJ2Yl9NdlNoODhLbkJOSWxmcVo0YmNDNDdtVVBiQm12TGc9PQ==",
  "url_encoded": "Z0FBQUFBQm5Lak9ISFhVTkRjYk5DSUs3Szk2SGFLX25lMDFYd1Itbm9saFRnMVg4X214b055VHFOTjBKUTZ3RXJOcURFbVNEdXZjaWR2V3d5VFpMTUpvek9lajJEMlRuaDRmcl8zTkJEZGF3ZjVwSlduMWkwQnA1NWRXcldPVHIwaW1rcm9YQU9Fd3NaUkFSYUZpMnp1Q3E3STNReTNCMThqMDBGaW1Kb2ltMWdmSDlZcW1VZUJ1bmZ2cXdXbmIzTVhYcmIyNkx5ZzI3RDBhZGVPTF8zZE5DZE1lVFZHdWFNZz09"
}
Explore Dataset Explore Row

Entry Information