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Is there any good literature giving further explenations about rapid-i beside the tutorials/manuals found on the website?
What other literature would help get one kick-started?
Hello and welcome to RapidMiner
I do not know a good online tutorial (googling ist not the problem, I do not know how to judge what is good or bad for a starter :-\ ), but here my suggestions:
A very lengthy video introduction you can find at the Google Tech Talks, i.e. a lecture about Data Mining (Part one starting
Beside this I am very conservative thinking that reading a book is necesary to understand what you are doing (Data Mining is a Science, somehow...). Here are my favourite ones (with Amazon link to ease it,not for supporting amazon
Data Mining: Techniques and Concepts
Data Mining: Practical Machine Learning Tools and Techniques
The second one was written using the Weka Tool, but the learning schemes of Weka are usable within RapidMiner,too.
hope this was helpful
The Gremlin in me also suggests....
"Fooled by Randomness" by Nasim Taleb
This is my litature list (some old colleages included
Barrow D. (1992) Making Money with Genetic Algorithms, in Proc. of the Fifth European Seminar on Neural Networks and Genetic Algorithms, IBC International Services, London.
Carbonell J. G., Langley P. (1990) Machine Learning, in Encyclopedia of Artificial Intelligence, S.C. Shapiro (ed.), vol. I, John Wiley & Sons, New York, pp. 464-488.
Clark P., Niblett T. (1989) The CN2 induction algorithm, in Machine Learning, 3, pp. 261-283.
Davis L. (1991) Handbook of Genetic Algorithms, Van Nostrand Rein¬hold, New York.
Eiben G. (1991) A Method for Designing Decision Support Systems for Operational Planning, thesis, Technische Universiteit Eindhoven.
Eshelman L.J., Schaffer J.D. (1991) Preventing Premature Convergence by Preventing Incest, in Proc. of the Fourth International Conference on Genetic Algorithms, Kaufmann, San Mateo, California, pp. 53 60.
Evans J. St. B. T. (1988) The knowledge elicitation problem: a psychological perspective, in Behaviour and Information Technology, 7, 2, pp. 111-130.
Gardner E.J., Simmons M.J., Snustad D.P. (1991) Principles of Genetics, 8th edition, John Wiley & Sons, New York.
Goldberg D.E. (1989) Genetic Algorithms in Search, Optimization & Machine Learning, Reading, Massachusetts.
Graf J., Nakhaeizadeh G. (1993) Recent Developments in Solving the Credit-Scoring Problem, Logistic and Learning for Quality Software, Management and Manufacturing, V.L. Plantamura, B. Soucek, G. Vissagio (eds), Wiley & Sons. New York.
Haasdijk E.W., Walker, R.F., Barrow, D., Gerrets, M.C. (1994) Genetic Algorithms in Business, Genetic Algorithms in Optimisation, Simulation and Modelling, J. Stender et al. (eds.), IOS Press, Amsterdam, pp. 157-184.
Haasdijk E.W. (1993) Sex Between Models: On Using Genetic Algorithms for Inductive Modelling, master's thesis, Dept. of Computer Science, University of Amsterdam.
Hillis W.D. (1992) Co-Evolving Parasites Improve Simulated Evolution as an Optimization Procedure, in Artificial Life II: Proceedings of the work¬shop on artificial life 1990, C.G. Langton, C. Taylor, J.D. Farmer, S. Rasmussen (eds), Addison-Wesley, Redwood City, California, pp. 313-324.
Kendall M.G. (1948) Rank correlation methods, Griffin, London.
Kingdon J. Ribeiro Filho J., Treleaven P. (1993) The GAME Programming Environment Architecture, in Parallel Genetic Algorithms: Theory and Applications, J. Stender (ed.), IOS Press, Amsterdam, pp. 85-92.
Koza J.R. (1992) Genetic Programming: On the Programming of Computers by Means of Natural Selection, MIT Press, Cambridge, Massachusetts.
Langley P., Simon H.A., Bradshaw G.L. (1990) Heuristics for Empirical Discovery, in Readings in Machine Learning, Kaufmann, San Mateo, California, pp. 356 372.
Mühlenbein H., Schomisch M., Born J. (1991) The Parallel Genetic Algorithm as Function Optimizer, in Proc. of the Fourth International Conference on Genetic Algorithms, Kaufmann, San Mateo, California, pp. 53 60.
Press W.H., Teukolsky S.A., Vetterling W.T., Flannery B.P. (1992) Numerical Recipes in C: The Art of Scientific Computing, 2nd edition, Cambridge University Press.
Quinlan J.R. (1986) Induction of Decision Trees, in Machine Learning, vol. 1, pp. 81-106.
Rumelhart D.E., McClelland J.L. & the PDP Research Group (1986) Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. I, MIT Press, Cambridge, Massachusetts.
Rumelhart D.E., Widrow B., Lehr M.A. (1994) The basic ideas in neural networks, in Com-munications of the ACM, 37, 3, pp. 86-92.
Statlog (1993) Machine learning, Neural and Statistical Classification, Deliverable 4.1 ESPRIT project 5170.
Walker R.F., Haasdijk, E.W., Gerrets, M.C. (1995) Credit evaluation Using a Genetic Algorithm, Intelligent Systems for Finance and Business, Goonatilake, S. and Treleaven, P. (eds.), John Wiley & Sons Ltd, New York, pp. 39-59.
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