outperformed the parametric models in terms of prediction performance. Also artificial neural nets, a popular machine learning … universal function approximator. A recent successful machine learning method is boosting. Boosting is a relative new method to … discuss the Machine Learning techniques used in this paper. Generally, in Machine Learning a model is trained (fit, calibrated …

In recent years the computers have shown to be a powerful tool in financial forecasting. Many machine learning … techniques have been utilized to predict movements in financial markets. Machine learning classifiers involve extending the past … investment. One of the main problems for any machine learning classifier is to deal with unbalanced classes. Specifically Genetic …

economy and wide engine operating range. Different advanced machine learning techniques, namely ELM (extreme learning machine …

parsing techniques, statistical machine learning offers many advantages for applied communication research. By using manually … analysis. In this paper, we briefly introduce the conceptual foundations of machine learning approaches to text classification …

physical (“white box”) models are reviewed according three-category classification. Then, we present the main machine learning … building thermal behaviour and mathematics-related ones, consisting in the implementation of prediction model thanks to machine … learning techniques. This paper proposes a detailed review and discussion of these works. First, the approaches based on …

decision rules. Consequently, the application of technical analysis in trading could produce high returns. Machine learning …

visible to a human eye, machine-learning methods have been developed to recognize persistent patterns in the data. In this … study, we develop a dynamic machine-learning method that designates traders in an anonymous electronic market into five …

the 1960s on, by linear statistical methods such as ARIMA models. More recently, machine learning models have drawn …. This chapter presents an overview of machine learning techniques in time series forecasting by focusing on three aspects …