
En este trabajo de investigación se presenta la técnica de Principal Component Analysis (PCA), y su aplicación práctica al aprendizaje automático (machine learning). La intención es abordar la problemática de la reducción dimensional o compresión de datos. A partir de un análisis intuitivo, se espera acercar a los economistas y otros profesionales de las ciencias sociales estas ideas que, generalmente, resultan ajenas a sus discusiones.
Social sciences (General), H1-99, Q1-390, Science (General), reducción dimensional, ingeniería, Science, Q, aprendizaje no supervisado, análisis de componentes principales
Social sciences (General), H1-99, Q1-390, Science (General), reducción dimensional, ingeniería, Science, Q, aprendizaje no supervisado, análisis de componentes principales
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
