But the same thing is that the leaves are each logistic regression model which is quite capable for analysis of dataset with dependent features and bounded magnitudes of time-series.
Homework and projects require implementing some of the algorithms and using existing toolkits for analysis of genomic datasets.
Yet even before Laney's article was published, an international consortium of over 200 organizations had already banded together (with funding from the European Union) to define and publish an open standard, CRISP-DM, for analysis of massive datasets.
Finally, our feature set has reached 76% accuracy in classification tests and 0.3 median absolute error for the regression model, which is the first result made for analysis of hitchhiking datasets.
In addition, several statistical analytical methods have been used for analysis of metabolomic datasets; for example, hierarchical cluster analysis (HCA) [39, 78], partial least squares discriminant analysis (PLS-DA) [52, 65], and batch-learning self-organizing map (BL-SOM) [43, 44, 54].
TNT is specifically designed for analysis of large datasets and permits ultra-fast supertree building.
The same phenomenon of unacceptable type I error was found by others when using FastEpistasis for analysis of real datasets.
Recently, Meyer et al. (2008) introduced the metagenome rapid annotation using subsystem technology (MG-RAST) server for analysis of metagenomic datasets.
