Application of Machine Learning Ensemble Methods to ASTRI Mini-Array Cherenkov Event Reconstruction

Ensemble Methods in Machine Learning

Ensemble methods are learning algorithms that construct a set of classi ers and then classify new data points by taking a weighted vote of their predictions The original ensemble method is Bayesian aver aging but more recent algorithms include error correcting output coding Bagging and boosting This paper reviews these methods and explains why ensembles can often perform better than any single ...

Fault Detection of Anti-friction Bearing using Ensemble Machine Learning Methods

Anti-Friction Bearing (AFB) is a very important machine component and its unscheduled failure leads to cause of malfunction in wide range of rotating machinery which results in unexpected downtime and economic loss. In this paper, ensemble machine learning techniques are demonstrated for the detection of different AFB faults. Initially, statistical features were extracted from temporal vibratio...

Ensemble Methods – Classifier Combination in Machine Learning

The last ten years have seen a research explosion in machine learning. The rapid growing is largely driven by the following two forces. First, separate research communities in symbolic machine learning, computational learning theory, neural network, statistics and pattern recognition have discovered one another and begun to work together. Second, machine learning technologies are being applied ...

Dimension Reduction Using Rule Ensemble Machine Learning Methods: A Numerical Study of Three Ensemble Methods

Ensemble methods for supervised machine learning have become popular due to their ability to accurately predict class labels with groups of simple, lightweight “base learners.” While ensembles offer computationally efficient models that have good predictive capability they tend to be large and offer little insight into the patterns or structure in a dataset. We consider an ensemble technique th...

Ensemble machine learning methods for acoustic modeling of speech