Cantitate/Preț
Produs

Advances in Intelligent Data Analysis

Editat de David J. Hand, Joost N. Kok, Michael R. Berthold
en Limba Engleză Paperback – 28 iul 1999

Preț: 74672 lei

Preț vechi: 93340 lei
-20%

Puncte Express: 1120

Carte tipărită la comandă

Livrare economică 08-22 iulie

Livrare prin curier în România Termenul estimat este afișat lângă disponibilitate.
Transport gratuit pentru acest produs Plată online sau ramburs, în funcție de opțiunile comenzii.
Retur gratuit în 14 zile Comandă securizată și suport în română.

Specificații

ISBN-13: 9783540663324
ISBN-10: 3540663320
Pagini: 556
Ilustrații: XII, 544 p.
Dimensiuni: 155 x 235 x 30 mm
Greutate: 0.83 kg
Ediția:1999
Editura: Springer
Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

Learning.- From Theoretical Learnability to Statistical Measures of the Learnable.- ALM: A Methodology for Designing Accurate Linguistic Models for Intelligent Data Analysis.- A “Top-Down and Prune” Induction Scheme for Constrained Decision Committees.- Mining Clusters with Association Rules.- Evolutionary Computation to Search for Strongly Correlated Variables in High-Dimensional Time-Series.- The Biases of Decision Tree Pruning Strategies.- Feature Selection as Retrospective Pruning in Hierarchical Clustering.- Discriminative Power of Input Features in a Fuzzy Model.- Learning Elements of Representations for Redescribing Robot Experiences.- “Seeing“ Objects in Spatial Datasets.- Intelligent Monitoring Method Using Time Varying Binomial Distribution Models for Pseudo-Periodic Communication Traffic.- Visualization.- Monitoring Human Information Processing via Intelligent Data Analysis of EEG Recordings.- Knowledge-Based Visualization to Support Spatial Data Mining.- Probabilistic Topic Maps: Navigating through Large Text Collections.- 3D Grand Tour for Multidimensional Data and Clusters.- Classification and Clustering.- A Decision Tree Algorithm for Ordinal Classification.- Discovering Dynamics Using Bayesian Clustering.- Integrating Declarative Knowledge in Hierarchical Clustering Tasks.- Nonparametric Linear Discriminant Analysis by Recursive Optimization with Random Initialization.- Supervised Classification Problems: How to Be Both Judge and Jury.- Temporal Pattern Generation Using Hidden Markov Model Based Unsupervised Classification.- Exploiting Similarity for Supporting Data Analysis and Problem Solving.- Multiple Prototype Model for Fuzzy Clustering.- A Comparison of Genetic Programming Variants for Data Classification.- Fuzzy Clustering Based onModified Distance Measures.- Building Classes in Object-Based Languages by Automatic Clustering.- Integration.- Adjusted Estimation for the Combination of Classifiers.- Data-Driven Theory Refinement Using KBDistAl.- Reasoning about Input-Output Modeling of Dynamical Systems.- Undoing Statistical Advice.- A Method for Temporal Knowledge Conversion.- Applications.- Intrusion Detection through Behavioral Data.- Bayesian Neural Network Learning for Prediction in the Australian Dairy Industry.- Exploiting Sample-Data Distributions to Reduce the Cost of Nearest-Neighbor Searches with Kd-Trees.- Pump Failure Detection Using Support Vector Data Descriptions.- Data Mining for the Detection of Turning Points in Financial Time Series.- Computer-Assisted Classification of Legal Abstracts.- Sequential Control Logic Inferring Method from Observed Plant I/O Data.- Evaluating an Eye Screening Test.- Application of Rough Sets Algorithms to Prediction of Aircraft Component Failure.- Media Mining.- Exploiting Structural Information for Text Classification on the WWW.- Multi-agent Web Information Retrieval: Neural Network Based Approach.- Adaptive Information Filtering Algorithms.- A Conceptual Graph Approach for Video Data Representation and Retrieval.