Machine Learning Process

To understand the machine learning process and learning concepts... 

By combining clustering with a machine learning process, we could be able to predict the development of physical autonomy loss or mental autonomy loss in elderly people over time. To reach this objective, we use machine learning approach based on grammar inference in order to infer a probabilistic automaton. In the article, we only present the patients profiles evolution regarding to upper body functional disorders (cognitive impairment). 

Figure 9-1. Machine learning and the disciplines involved in this process.

Sheikh, A.Y. and Jones, A.G., 1997. Crystallization process optimisation through a revised machine learning methodology. American Institution of Chemical Engineers Journal, 43, 1448-1457. 

The high dimensional nature of LIBS signals can lead to several computational issues when used in conjunction with many machine learning techniques. Dimensionality reduction is the process by which the high dimensional signals are mapped into a lower dimensional space. The resulting lower dimensional space can enable more robust performance when used in conjunction with pattern recognition techniques. 

The benefits of presenting chemoinformatics data in an intuitive manner make Prometheus an obvious asset to researchers. The customizable software being developed for chemistry of natural products should enable scientists to rapidly process large spectroscopic data sets and solve the structure of new isolates more efficiently. The machine learning aspect of the medical informatics component holds significant future promise. Additionally, the characterization aspect of Rx s toolkit is particularly attractive for medical practitioners. Fully developing the early warning system component of Rx s toolkit would increase its usefulness in ICU s and the medical community. 

Machine learning is defined as the use of algorithms to generate a model from data, which is one step in the knowledge discovery process, applied in the context... 

Keane, M. T., and Brayshaw, M. (1988). The incremental analogical machine a computational model of analogy. In D. Sleeman (ed.), Third European Working Session on Machine learning (pp. 53-62). San Mateo, Calif. Kaufmann. Kendon, K. (1980). Gesticulation and speech two aspects of the process of utterance. In M. R. Key (ed.), The relation between verbal and nonverbal communication (pp. 207-227). The Hague Mouton. 

---