Comments (1)
@alvarag @jjrodriguez
he actualizado el codigo en Github:
https://github.com/Dguipla/TFM-SemiSup/tree/main/notebooks/SemiSupervised No estaria en esta version la comparativa de SelfTraining y CoTraining con algunos datasets del paper de triguero, lo tengo pendiente
PD: En breve os comparto la documentacion con overleaf
from tfm-semisup.
Related Issues (20)
- SelfTrainning - Calculos de probabilidades por los clasificadores base
- Nueva Clase para SelfTraining
- Self Trainning --> Implementacion de pipeline para cada Conjunto de datos + modelo SelfTrainnig
- SelfTraining --> Lanzamiento de todos los Pipelines + SelfTraining- modelos (para cada clasificador :DT, LR....)
- Crear la clase del "desetiquetador" HOT 16
- Crear Class para los datos de SemiSupervisado
- modificacion de los for/s de las funciones calculo de resultados por maps
- Parte 4 (Co-Training Implementacion)
- Duda - Paper Triguero-Garcia-Herrera (Keel) y sus implementaciones para poder comparar con Spark y Self/CoTraining HOT 1
- Overleaf - Memoria - Compartida
- Parte 5 Resultados
- Comparativa Self/CoTraining Spark con Keel (paper Triguero)
- Parte 5 (Resultados y Memoria Final)
- Reunión seguimiento
- Scatter - Duda (Keel vs Spark) HOT 3
- Memoria
- Completar resultados con powerBI
- Crear una biblioteca de Spark HOT 14
- Dashboard publicado online con PowerBI HOT 2
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