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Statistical Learning and Data Sciences

Statistical Learning and Data Sciences


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About the Book

Learning with Intelligent Teacher: Similarity Control and Knowledge Transfer.- Statistical Inference Problems and Their Rigorous Solutions.- Feature Mapping Through Maximization of the Atomic Interclass Distances.- Adaptive Design of Experiments for Sobol Indices Estimation Based on Quadratic Metamodel.- GoldenEye++: A Closer Look into the Black Box.- Gaussian Process Regression for Structured Data Sets.- Adaptive Design of Experiments Based on Gaussian Processes.- Forests of Randomized Shapelet Trees.- Aggregation of Adaptive Forecasting Algorithms Under Asymmetric Loss Function.- Visualization and Analysis of Multiple Time Series by Beanplot PCA.- Recursive SVM Based on TEDA.- RDE with Forgetting: An Approximate Solution for Large Values of k with an Application to Fault Detection Problems.- Sit-to-Stand Movement Recognition Using Kinect.- Additive Regularization of Topic Models for Topic Selection and Sparse Factorization.- Social Web-Based Anxiety Index's Predictive Information on S&P 500 Revisited.- Exploring the Link Between Gene Expression and Protein Binding by Integrating mRNA Microarray and ChIP-Seq Data.- Evolving Smart URL Filter in a Zone-Based Policy Firewall for Detecting Algorithmically Generated Malicious Domains.- Lattice-Theoretic Approach to Version Spaces in Qualitative Decision Making.- A Comparison of Three Implementations of Multi-Label Conformal Prediction.- Modifications to p-Values of Conformal Predictors.- Cross-Conformal Prediction with Ridge Regression.- Handling Small Calibration Sets in Mondrian Inductive Conformal Regressors.- Conformal Anomaly Detection of Trajectories with a Multi-class Hierarchy.- Model Selection Using Efficiency of Conformal Predictors.- Confidence Sets for Classification.- Conformal Clustering and Its Application to Botnet Traffic.- Interpretation of Conformal Prediction Classification Models.- New Frontiers in Data Analysis for Nuclear Fusion Confinement Regime Identification Using Artificial Intelligence Methods.- How to Handle Error Bars in Symbolic Regression for Data Mining in Scientific Applications.- Applying Forecasting to Fusion Databases.- Computationally Efficient Five-Class Image Classifier Based on Venn Predictors.- SOM and Feature Weights Based Method for Dimensionality Reduction in Large Gauss Linear Models.- Geometric Data Analysis Assigning Objects to Classes of a Euclidean Ascending Hierarchical Clustering.- The Structure of Argument: Semantic Mapping of US Supreme Court Cases.- Supporting Data Analytics for Smart Cities: An Overview of Data Models and Topology.- Manifold Learning in Regression Tasks.- Random Projection Towards the Baire Metric for High Dimensional Clustering.- Optimal Coding for Discrete Random Vector.


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Product Details
  • ISBN-13: 9783319170909
  • Publisher: Springer
  • Publisher Imprint: Springer
  • Edition: 2015 ed.
  • Language: English
  • Returnable: Y
  • Spine Width: 24 mm
  • Weight: 689 gr
  • ISBN-10: 3319170902
  • Publisher Date: 28 May 2015
  • Binding: Paperback
  • Height: 234 mm
  • No of Pages: 444
  • Series Title: Lecture Notes in Computer Science
  • Sub Title: Third International Symposium, Slds 2015
  • Width: 156 mm


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