Books by Chandan Srivastava

This book is based on the basis that clustering and neural networks methods. The clustering algorithms (k-means, and k-medoids) are describe the analysis on noise data i.e. preclassification for robust model development. The better choice of cluster are forming by Euclidean statistical clustering algorithms, are able to preclassified data into significant groups. We assume that both methods are better predicted on different example in real analysis. The recurrent backpropagation is one of the best optimization techniques for minimizing the error and achieve the best optimal result. Since we have input unit, output unit, and eventually hidden unit; we could say that this is supervised optimization learning process. The optimization process to minimizing the error and get the activated network till that all weight of the network are going to reach equilibrium state). This process usually take more time because every output of network add-up with input again and train network (weight) to reach the equilibrium state (optimal solution).Reported results and graphical user interface (GUI) snapshot, showing algorithms are integrated well in software package (simulator).

This book is based on the basis that machine learningalgorithms and rank based statistical methods are abetter choice to develop a robust model in logicalsituations. We designed experimental setup for datacollection, developed unique class of model includingvariable selection, and detection methods. Theselected significant variables provide a unique classof model for all six participants. We emphasize thebest selected variables have good information formodel development, and each selected variable have noerror i.e.; AUC=1, with forward selection and supportvector data description classifier. Basically, wedeveloped a unique class of model using six differentclasses of subjects, predicting elderly fallprevention, and after doing external validation withseventh class of subject, we reached a uniquesolution. Sections one is research introduction,section two is all about research design and dataanalysis, section three and four give extensivedevelopment of model for variable selection and oneclass classifier. Then finally given the conclusionand future aspect of whole study.