Rank-Based Methods for Shrinkage and Selection. A. K. Md. Ehsanes Saleh

12.1 RNN-ridge algorithm.Table 12.2 Interpretation of the confusion matrix.Table 12.3 Confusion matrix for Titanic data sets using RLR...Table 12.4 Number of correct predictions (percentages) and AUROC of LNN-ridge.Table 12.5 Input (x_ij), output (y_i) and predicted values p~(x_i) for the image classification problem.Table 12.6 Confusion matrices for RNNs and LNNs (test size = 35).Table 12.7 Accuracy metrics for RNNs vs. LNNs (test size = 35).Table 12.8 Train/test set accuracy for LNNs. F₁ score is associated with the test set.Table 12.9 Train/test set accuracy for RNNs. F₁ score is associated with the test set.Table 12.10 Confusion matrices for RNNs and LNNs (test size = 700).Table 12.11 Accuracy metrics for RNNs vs. LNNs (test size = 700).Table 12.12 MNIST training with 0 outliers.Table 12.13 MNIST training with 90 outliers.Table 12.14 MNIST training with 180 outliers.Table 12.15 MNIST training with 270 outliers.Table 12.16 Table of responses and probability outputs.

      Guide

      1  Cover

      2  Title page

      3  Copyright

      4  Dedication

      5  List of Figures

      6 Table of Contents

      7  List of Figures

      8  List of Tables

      9  Foreword

      10  Preface

      11  Begin Reading

      12  Bibliography

      13  Author Index

      14  Subject Index

      15  End User License Agreement

      Pages

      1  i

      2  ii

      3  iii

      4  iv

      5  v

      6  vi

      7  vii

      8 viii

      9  ix

      10  x

      11  xi

      12  xii

      13  xiii

      14  xiv

      15  xv

      16  xvi

      17  xvii

      18  xviii

      19  xix

      20  xx

      21  xxi

      22  xxii

      23  xxiii

      24  xxiv

      25  xxv

      26  xxvi

      27  xxvii

      28  xxviii

      29  xxix

      30  xxx

      31  xxxi

      32  1

      33  2

      34  3

      35  4

      36  5

      37  6

      38  7

      39  8

      40  9

      41