Documentos de Muoz-Romero S. | REDI

Regresar

Mostrando 4 resultados de: 4

Filtros aplicados

Palabras Claves: "feature selection"

Subtipo de publicación

Conference Object(1)

Publisher

Applied Sciences (Switzerland)(1)

Expert Systems with Applications(1)

Pattern Recognition(1)

Proceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020(1)

Área temáticas

Enfermedades(2)

Análisis numérico(1)

Ciencias de la computación(1)

Fisiología humana(1)

Área de conocimiento

Aprendizaje automático(3)

Ciencias de la computación(1)

Epidemiología(1)

Estadísticas(1)

Objetivos de Desarrollo Sostenible

ODS 17: Alianzas para lograr los objetivos(3)

ODS 9: Industria, innovación e infraestructura(3)

ODS 3: Salud y bienestar(2)

ODS 8: Trabajo decente y crecimiento económico(2)

ODS 16: Paz, justicia e instituciones sólidas(1)

Año de Publicación

Origen

Palabras Claves

Explainable machine learning(2)

interpretability(2)

Autoencoders(1)

CORRESPONDENCE ANALYSIS(1)

Chronic conditions(1)

Finding Associations among Chronic Conditions by Bootstrap and Multiple Correspondence Analysis

Conference Object

Abstract: Contemporary societies are suffering from negative population growth, with the consequent population

Palabras claves:

bootstrap resampling, Chronic conditions, CORRESPONDENCE ANALYSIS, feature selection

Alonso-Arteaga N., Jose Luis Rojo-Álvarez, Lopez-Fajardo I.C., Mora-Jimnez I., Muoz-Romero S., Rubio-Sánchez M., Soguero-Ruiz C.

Informative variable identifier: Expanding interpretability in feature selection

Abstract: There is nowadays an increasing interest in discovering relationships among input variables (also ca

Palabras claves:

classification, Explainable machine learning, feature selection, interpretability, Resampling

Gorostiaga A., Jose Luis Rojo-Álvarez, Mora-Jimnez I., Muoz-Romero S., Soguero-Ruiz C.

Multivariate feature selection and autoencoder embeddings of ovarian cancer clinical and genetic data

Abstract: Although certain genetic alterations have been defined as predictive and prognostic biomarkers in th

Palabras claves:

Autoencoders, Clinical Data, Feature Extraction, feature selection, genetic data, Ovarian Cancer, Platinum-resistant, Platinum-sensitive

Barquin A., Bote-Curiel L., Garcia-Donas J., Jose Luis Rojo-Álvarez, Muoz-Romero S., Ruiz-Llorente S., Yagüe-Fernández M.

On the Black-Box Challenge for Fraud Detection Using Machine Learning (I): Linear Models and Informative Feature Selection

Abstract: Artificial intelligence (AI) is rapidly shaping the global financial market and its services due to

Palabras claves:

cbkp_redit fraud detection, Explainable machine learning, feature selection, interpretability

Chaquet-Ulldemolins J., Gimeno-Blanes F.J., Jose Luis Rojo-Álvarez, Moral-Rubio S., Muoz-Romero S.