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Rule-Based Forecasting: Using domain knowledge in time series extrapolation

Armstrong, J. Scott; Adya, Monica; Collopy, Fred - 2001

Rule-Based Forecasting (RBF) is an expert system that uses judgment to develop and apply rules for combining … extrapolations. The judgment comes from two sources, forecasting expertise and domain knowledge. Forecasting expertise is based on … absent, RBF neither improves nor harms forecast accuracy. Some of RBF?s rules can be used with traditional extrapolation …

Persistent link: https://www.econbiz.de/10009484509

Development of models for short-term load forecasting using artificial neural networks

Amakali, Simaneka - 2008

forecasting accuracy. This thesis developed models for STLF using ANNs approach. The evolved models are intended to be a basis for …

Persistent link: https://www.econbiz.de/10009447198

Modeling Purposeful Adaptive Behavior with the Principle of Maximum Causal Entropy

Ziebart, Brian D. - 2010

thesis, we introduce the principle of maximum causal entropy, a general technique for applying information theory to decision …

Persistent link: https://www.econbiz.de/10009441102

AN ANALYSIS OF MISCLASSIFICATION RATES FOR DECISION TREES

Zhong, Mingyu - 2007

The decision tree is a well-known methodology for classification and regression. In this dissertation, we focus on the minimization of the misclassification rate for decision tree classifiers. We derive the necessary equations that provide the optimal tree prediction, the estimated risk of the...

Persistent link: https://www.econbiz.de/10009431076

Machine learning in credit risk: measuring the dilemma between prediction and supervisory cost

Alonso, Andrés; Carbó, José Manuel - 2020

Informes recientes muestran la creciente adopción en el sector financiero de técnicas de aprendizaje automático o machine learning (ML) en la gestión del riesgo de crédito. En este entorno, los supervisores se encuentran ante el reto de permitir que se maximicen las oportunidades derivadas...

Persistent link: https://www.econbiz.de/10012525231

Artificial intelligence in financial services

Fernández Bedoya, Ana

Artículo de revista ; The use of artificial intelligence tools has escalated recently in all sectors of the economy owing, among other factors, to the growing volume of digital data and higher computational capacity. Major benefits may be reaped from applying these tools to the provision of...

Persistent link: https://www.econbiz.de/10012532407

Accuracy of explanations of machine learning models for credit decisions

Alonso, Andrés; Carbó Martinez, José Manuel

Uno de los principales retos en el uso de modelos de aprendizaje automático, o machine learning en inglés (ML), en finanzas es cómo explicar sus resultados. Recientemente han aparecido técnicas de interpretabilidad con este objetivo, pero existe discusión sobre su fiabilidad. En este...

Persistent link: https://www.econbiz.de/10013267753

Inteligencia artificial y finanzas: una alianza estratégica

Alonso, Andrés; Carbó Martinez, José Manuel

, and transforming fundamental aspects of both financial institutions and supervisors. In this paper we review the main …

Persistent link: https://www.econbiz.de/10013414504

A framework for managing global risk factors affecting construction cost performance

Baloi, Daniel - 2002

decision theory, and their practical applicationby construction contractors. The main reason behind the lack of use is that …

Persistent link: https://www.econbiz.de/10009461257

Feedback-labelling synergies in judgmental stock price forecasting

Goodwin, Paul; Önkal-Atay, Dilek; Thomson, Mary E.; … - 2004

Research has suggested that outcome feedback is less effective than other forms of feedback in promoting learning by users of decision support systems. However, if circumstances can be identified where the effectiveness of outcome feedback can be improved, this offers considerable advantages,...

Persistent link: https://www.econbiz.de/10009435352