dotnet / dotnet/machinelearning-modelbuilder
Request: Text Clustering
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- Dockerfile
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Descripción
**Is your feature request related to a problem? Please describe.**
Sometimes we have a set of uncategorized texts. Either we do not care about categorization models, or we want to create a model to help categorization. Examples could be: products, credit card transaction, climate measurements, customer feedback etc.
In this request I am mainly talking about text based clustering.
**Describe the solution you'd like**
I would like to use Model Builder to cluster a set of texts, such as customer feedback.
**Describe alternatives you've considered**
Manually create the clustering code from samples. Perhaps, Model Builder could also help only with downloading sample code, or copy-paste snippets? Not ideal, but better than needing to search online.
**Additional context**
In contrast to other scenarios, this scenario would ideally also return the final clusters for each item in the input file.
This file could have multiple purposes, but considering building models, I think it is first step towards classification model.
However, if this were the only use of it, then users should use other data analysis tools. I believe the clusteration model itself will be useful for many users. We do not always need, or even can, categorize items.
Guía de contribución
No hay ninguna guía de contribución indexada para este repositorio
Línea de trabajo
No se han identificado archivos, pruebas ni puntos de entrada. Empieza revisando los escenarios existentes de Model Builder y cómo gestionan las entradas de texto; para darlo por terminado sería necesario definir un flujo de trabajo de clustering que produzca clústeres para cada elemento de entrada y aclare si se incluye el código de ejemplo generado.
Escrito por el modelo de indexación a partir del texto del issue.
Evaluación
- Stack tecnológico
- machine-learning
- Área
- machine-learning
- Tipo de issue
- Nueva funcionalidad
- Dificultad
- 5/5
- Tiempo estimado
- Más de una semana
- Estado de actividad
- Estancado
- Claridad
- Necesita aclaración
- Aptitud para principiantes
- 25/100