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Machine learning is a novel discipline concerned with the analysis of large and multiple variables data. It involves computationally intensive methods, like factor analysis, cluster analysis, and discriminant analysis. It is currently mainly the domain of computer scientists, and is already commonly used in social sciences, marketing research, operational research and applied sciences. It is virtually unused in clinical research. This is probably due to the traditional belief of clinicians in clinical trials where multiple variables are equally balanced by the randomization process and are not further taken into account. In contrast, modern computer data files often involve hundreds of variables like genes and other laboratory values, and computationally intensive methods are required. This book was written as a hand-hold presentation accessible to clinicians, and as a must-read publication for those new to the methods. |
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Samba Installation, Configuration, and Sizing GuideSamba is the very popular freeware that turns your AIX machine into a resources server for your PC clients. This book explains how to install and set up a Samba server, how to declare file and printer shares, and how to choose the best security model that fits your needs.
But it won’t cover all the features of Samba in detail. Many... | | | | Principles of Solid MechanicsThere is no area of applied science more diverse and powerful than the mechanics of deformable solids nor one with a broader and richer history. From Galileo and Hooke through Coulomb, Maxwell, and Kelvin to von Neuman and Einstein, the question of how solids behave for structural applications has been a basic theme for physical research exciting... |
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