Diferencia entre revisiones de «Jornada GIC random forests 2012-01-27»
De Grupo de Inteligencia Computacional (GIC)
| Línea 15: | Línea 15: | ||
* Borja Fernandez-Gauna: learning areas of expertise [[media:Borja-Learning-the-areas-of-expertise-of-classifiers-in-an-ensemble.pdf | presentation]] | * Borja Fernandez-Gauna: learning areas of expertise [[media:Borja-Learning-the-areas-of-expertise-of-classifiers-in-an-ensemble.pdf | presentation]] | ||
* Borja Ayerdi: random feature weights | * Borja Ayerdi: random feature weights | ||
* Jose Manuel Lopez-Guede: pruning con reinforcement learning [http://www.ehu.es/ccwintco/groupware/webdav.php/apps/phpbrain/104/partalas-2009-pruning-ensemble-reinforcement-learning-Presentation.pdf presentation] | |||
* Borja Ayerdi: statistical pruning [http://www.ehu.es/ccwintco/groupware/webdav.php/apps/phpbrain/554/sesion_especial_random_forest.pdf diap ] | |||
== distribución de articulos a presentar == | == distribución de articulos a presentar == | ||
Revisión del 20:13 26 ene 2012
objetivo
El objetivo de la jornada es hacer un repaso al estado del arte sobre random forests (y sistemas de clasificación basados en ensambles?). El metodo de trabajo consiste en la presentación por parte de todos los presentes de resumenes de articulos recientes
orden de las presentaciones
- Josu Maiora: tutorial de Criminisi, clasificiacion y regresion slides
- Alexandre Savio: breiman slides_sinrefs
- Iñigo Barandiaran: prehistoria ??
- Maite Termenon: theoretical study Slides
- Ana I. Gonzalez: experimental comparison on ensembles of trees review
- Darya Chyzhyk: incremental ensembles |---Slides
- Ramón Moreno: overfitting cautious Slides
- Elsa Fernandez: seleccion de variables usando RF Slides
- Borja Fernandez-Gauna: learning areas of expertise presentation
- Borja Ayerdi: random feature weights
- Jose Manuel Lopez-Guede: pruning con reinforcement learning presentation
- Borja Ayerdi: statistical pruning diap
distribución de articulos a presentar
- Ana I. Gonzalez
- Josu Maiora
- Borja Fernandez-Gauna
- learning areas of expertise [9] presentation
- building by reward-punishment [10] presentation
- Jose Manuel Lopez-Guede
- data mining [11] presentation
- pruning con reinforcement learning [12] presentation
- Darya Chyzhyk
- incremental ensembles [14] |---Slides
- subspace projections [15] |---Slides, [16] |---Slides
- Maite Termenon
- Ion Marques
- ensembles from fuzzy clustering [27] presentation
- action detection [28] presentation
- Eider Sanchez
- dynamic ensemble [29] presentacion dynamic
- aplicaciones generales [30] presentacion aplicaciones
- Alexandre Savio:
- Ting Agregacion de subespacios de features [31] -- > no llega late slides
- comparison [32] slides slides_sinrefs
- breiman [33] slides slides_sinrefs
referencias
- Groupware general [34]
aplicaciones [50]
- analisis de accidentes [51]
- ingenieria mecanica [52]
- ingenieria financiera [53], [54], [55], [56], [57], [58], [59], [60], [61], [62]
- biologicas, medicas y ecologicas [66], [67], [68], [69], [70], [71], [72], [73], [74], [75], [76], genomics [77], [78], [79], [80], breast cancer [81], [82], [83], cardiac arrythmia [84], [85], [86], [87], soil texture [88], [89], apendicitis [90], pulmones [91], cancer [92], glaucoma [93], [94], colon cells [95], higado [96], piel [97], de todo ?? [98], celulas [99], ultrasonidos [100], mental fatigue [101], cornea [102]
- data mining [116],
- neurociencias [117], [118], [119], fMRI [120], [121], [122], [123], [124], [125], [126], brain extraction [127]
- imagen de reconocimiento remoto, remote sensing, [128], [129], [130], [131], [132], land slides [133], [134], [135], [136], [137], hypespectral data [138], [139], SAR [140]
- pattern recognition [141], [142], biometric data [143], hadwritng [144], signature [145], objetos y acciones [146], [147], [148], visual concept [149], face and action [150]
- intrusion detection [151]
