Machine learning

Golding D E 1989 Genetic Aigorithms in Search, Optimization and Machine Learning (Reading, MA Addison Wesley)... 

D.E. Goldberg, Genetic Algorithms in Search, Optimi2ation and Machine Learning, Addison-Wesley, New York, 1989. 

Gelemter and Rose [25] used machine learning techniques Chapter IX, Section 1.1 of the Handbook) to analyze the reaction center. Based on the functionalities attached to the reaction center, the method of conceptual clustering derived the features a reaction needed to possess for it to be assigned to a certain reaction type. A drawback of this approach was that it only used topological features, the functional groups at the reaction center, and its immediate environment, and did not consider the physicochemical effects which are so important for determining a reaction mechanism and thus a reaction type. 

T.M. Mitchell, Machine Learning. McGraw-Hill, New York, 1997-... 

To understand the recommendations for structure descriptors in order to be able to apply them in QSAR or drug design in conjunction with statistical methods or machine learning techniques. 

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

In recent decades, computer scientists have tried to provide computers with the ability to learn. This area of research was summarized under the umbrella term "machine learning . Today machine learning is defined as "the study of computer algorithms that improve automatically through experience [1]. 

Figure 9-1 shows the disciplines that contribute to machine learning techniques. 

The area of machine learning is thus quite broad, and different people have different notions about the domain of machine learning and what kind of techniques belong to this field. We will meet a similar problem of defining an area and the techniques involved in the field of "data mining , as discussed in Section 9.8. We will use the term "machine learning in this chapter to collect aU the methods that involve learning from data. 

One application of machine learning is that a system uses sample data to build a model which can then be used to analyze subsequent data. Learning from exam-... 

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

The following sections present a more detailed description of the methods mentioned above. An overview of machine learning techniques in chemistry is given in Chapter IX, Section 1 in the Handbook. 

It extends the usage of statistical methods and combines it with machine learning methods and the application of expert systems. The visualization of the results of data mining is an important task as it facilitates an interpretation of the results. Figure 9-32 plots the different disciplines which contribute to data mining. 

Machine Learning ------M Data Mining [<-------- Expert Systems... 

R. S. Michalski, R. E. Stepp. Learning from Observation Ganceptual Clustering, in Machine Learning An Artificial Intelligence Approach, R.S. Michalski, f.G. CarboneU, T.M. Mitchell (Eds.), Morgan Kauffmatm, San Mateo, GA, 1983, pp. 331-363. 

One of the first attempts to build a knowledge base for synthetic organic reactions was made by Gelernter s group, through inductive and deductive machine learning [1]. Important work on this topic was also performed by Funatsu and his group [2]. 

P Baku, S Bnmak. Biomformatics The Machine Learning Approach. Cambridge, MA MIT Press, 1998. 

G Bobs, L Pace, F Fabrocim. A machine learning approach to computer-aided molecular design. J Comput Aided Mol Des 5(6) 617-628, 1991. 

D. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, Reading (Mass.), 1989. 2-263 W. Braun, G. Held, H.-P. Steinruck,... 

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