Introduction to pattern recognition and machine learning / by M Narasimha Murty & V Susheela Devi (Indian Institute of Science, India).

Format:

Book

Author/Creator:

Murty, M. Narasimha, author.

Devi, V. Susheela, author.

Series:

IISc lecture notes series ; 5.

IISc lecture notes series, 2010-2402 ; volume 5

Language:

English

Subjects (All):

Pattern recognition systems.

Machine learning.

Physical Description:

1 online resource (402 p.)

Place of Publication:

New Jersey : World Scientific, [2015]

Language Note:

English

Summary:

"This book adopts a detailed and methodological algorithmic approach to explain the concepts of pattern recognition. While the text provides a systematic account of its major topics such as pattern representation and nearest neighbour based classifiers, current topics — neural networks, support vector machines and decision trees — attributed to the recent vast progress in this field are also dealt with. Introduction to Pattern Recognition and Machine Learning will equip readers, especially senior computer science undergraduates, with a deeper understanding of the subject matter."-- Provided by publisher.

Contents:

""Table of Contents""; ""About the Authors""; ""Preface""; ""1. Introduction""; ""1. Classifiers: An Introduction""; ""2. An Introduction to Clustering""; ""3. Machine Learning""; ""Research Ideas""; ""2. Types of Data""; ""1. Features and Patterns""; ""2. Domain of a Variable""; ""3. Types of Features""; ""3.1. Nominal data""; ""3.1.1. Operations on nominal variables""; ""3.2. Ordinal data""; ""3.2.1. Operations possible on ordinal variables""; ""3.3. Interval-valued variables""; ""3.3.1. Operations possible on interval-valued variables""; ""3.4. Ratio variables""

""3.5. Spatio-temporal data""""4. Proximity measures""; ""4.1. Fractional norms""; ""4.2. Are metrics essential?""; ""4.3. Similarity between vectors""; ""4.4. Proximity between spatial patterns""; ""4.5. Proximity between temporal patterns""; ""4.6. Mean dissimilarity""; ""4.7. Peak dissimilarity""; ""4.8. Correlation coefficient""; ""4.9. Dynamic Time Warping (DTW) distance""; ""4.9.1. Lower bounding the DTW distance""; ""Research Ideas""; ""3. Feature Extraction and Feature Selection""; ""1. Types of Feature Selection""; ""2. Mutual Information (MI) for Feature Selection""

""3. Chi-square Statistic""""4. Goodman-Kruskal Measure""; ""5. Laplacian Score""; ""6. Singular Value Decomposition (SVD)""; ""7. Non-negative Matrix Factorization (NMF)""; ""8. Random Projections (RPs) for Feature Extraction""; ""8.1. Advantages of random projections""; ""9. Locality Sensitive Hashing (LSH)""; ""10. Class Separability""; ""11. Genetic and Evolutionary Algorithms""; ""11.1. Hybrid GA for feature selection""; ""12. Ranking for Feature Selection""; ""12.1. Feature selection based on an optimization formulation""; ""12.2. Feature ranking using F-score""

""12.3. Feature ranking using linear support vector machine (SVM) weight vector""""12.4. Ensemble feature ranking""; ""12.4.1. Using threshold-based feature selection techniques""; ""12.4.2. Evolutionary algorithm""; ""12.5. Feature ranking using number of label changes""; ""13. Feature Selection for Time Series Data""; ""13.1. Piecewise aggregate approximation""; ""13.2. Spectral decomposition""; ""13.3. Wavelet decomposition""; ""13.4. Singular Value Decomposition (SVD)""; ""13.5. Common principal component loading based variable subset selection (CLeVer)""; ""Research Ideas""

""4. Bayesian Learning""""1. Document Classification""; ""2. Naive Bayes Classifier""; ""3. Frequency-Based Estimation of Probabilities""; ""4. Posterior Probability""; ""5. Density Estimation""; ""6. Conjugate Priors""; ""Research Ideas""; ""5. Classification""; ""1. Classification Without Learning""; ""2. Classification in High-Dimensional Spaces""; ""2.1. Fractional distance metrics""; ""2.2. Shrinkage-divergence proximity (SDP)""; ""3. RandomForests""; ""3.1. Fuzzy random forests""; ""4. Linear Support Vector Machine (SVM)""; ""4.1. SVM-kNN""

""4.2. Adaptation of cutting plane algorithm""

Notes:

Description based upon print version of record.

Includes bibliographical references and index.

Description based on print version record.

ISBN:

1-68015-858-9

981-4335-46-0