Milan Stehlik, Basker Pant, Kumud Pant, K.R. Pardasani,
"Issues on Machine Learning for Prediction of Classes Among Molecular Sequences of Plants and Animals"
, in Theodore E. Simos, George Psihoyios, Ch. Tsitouras, Zacharias Anastassi: NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2012: International Conference of Numerical Analysis and Applied, Vol. 1479, Seite(n) 446-449, 2012
Original Titel:
Issues on Machine Learning for Prediction of Classes Among Molecular Sequences of Plants and Animals
Sprache des Titels:
Englisch
Original Buchtitel:
NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2012: International Conference of Numerical Analysis and Applied
Original Kurzfassung:
Nowadays major laboratories of the world are turning towards in-silico experimentation due to their ease, reproducibility and accuracy. The ethical issues concerning wet lab experimentations are also minimal in in-silico experimentations. But before we turn fully towards dry lab simulations it is necessary to understand the discrepancies and bottle necks involved with dry lab experimentations. It is necessary before reporting any result using dry lab simulations to perform in-depth statistical analysis of the data. Keeping same in mind here we are presenting a collaborative effort to correlate findings and results of various machine learning algorithms and checking underlying regressions and mutual dependencies so as to develop an optimal classifier and predictors.
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