000 | 05303nam a22006735i 4500 | ||
---|---|---|---|
001 | 978-3-540-44816-7 | ||
003 | DE-He213 | ||
005 | 20240423132514.0 | ||
007 | cr nn 008mamaa | ||
008 | 121227s2001 gw | s |||| 0|eng d | ||
020 |
_a9783540448167 _9978-3-540-44816-7 |
||
024 | 7 |
_a10.1007/3-540-44816-0 _2doi |
|
050 | 4 | _aQA76.9.D3 | |
072 | 7 |
_aUN _2bicssc |
|
072 | 7 |
_aCOM021000 _2bisacsh |
|
072 | 7 |
_aUN _2thema |
|
082 | 0 | 4 |
_a005.74 _223 |
245 | 1 | 0 |
_aAdvances in Intelligent Data Analysis _h[electronic resource] : _b4th International Conference, IDA 2001, Cascais, Portugal, September 13-15, 2001. Proceedings / _cedited by Frank Hoffmann, David J Hand, Niall M. Adams, Douglas Fisher, Gabriela Guimaraes. |
250 | _a1st ed. 2001. | ||
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2001. |
|
300 |
_aXII, 388 p. _bonline resource. |
||
336 |
_atext _btxt _2rdacontent |
||
337 |
_acomputer _bc _2rdamedia |
||
338 |
_aonline resource _bcr _2rdacarrier |
||
347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aLecture Notes in Computer Science, _x1611-3349 ; _v2189 |
|
505 | 0 | _aThe Fourth International Symposium on Intelligent Data Analysis -- Feature Characterization in Scientific Datasets -- Relevance Feedback in the Bayesian Network Retrieval Model: An Approach Based on Term Instantiation -- Generating Fuzzy Summaries From Fuzzy Multidimensional Databases -- A Mixture-of-Experts Framework for Learning from Imbalanced Data Sets -- Predicting Time-Varying Functions with Local Models -- Building Models of Ecological Dynamics Using HMM Based Temporal Data Clustering — A Preliminary Study -- Tagging with Small Training Corpora -- A Search Engine for Morphologically Complex Languages -- Errors Detection and Correction in Large Scale Data Collecting -- A New Framework to Assess Association Rules -- Communities of Interest -- An Evaluation of Grading Classifiers -- Finding Informative Rules in Interval Sequences -- Correlation-Based and Contextual Merit-Based Ensemble Feature Selection -- Nonmetric Multidimensional Scaling with Neural Networks -- Functional Trees for Regression -- Data Mining with Products of Trees -- S 3Bagging: Fast Classifier Induction Method with Subsampling and Bagging -- RNA-Sequence-Structure Properties and Selenocysteine Insertion -- An Algorithm for Segmenting Categorical Time Series into Meaningful Episodes -- An Empirical Comparison of Pruning Methods for Ensemble Classifiers -- A framework for Modelling Short, High-Dimensional Multivariate Time Series: Preliminary Results in Virus Gene Expression Data Analysis -- Using Multiattribute Prediction Suffix Graphs for Spanish Part-of-Speech Tagging -- Self-Supervised Chinese Word Segmentation -- Analyzing Data Clusters: A Rough Sets Approach to Extract Cluster-Defining Symbolic Rules -- Finding Polynomials to Fit Multivariate Data Having Numeric and Nominal Variables -- Fluent Learning: Elucidatingthe Structure of Episodes -- An Intelligent Decision Support Model for Aviation Weather Forcasting -- MAMBO: Discovering Association Rules Based on Conditional Independencies -- Model Building for Random Fields -- Active Hidden Markov Models for Information Extraction -- Adaptive Lightweight Text Filtering -- General Algorithm for Approximate Inference in Multiply Sectioned Bayesian Networks -- Investigating Temporal Patterns of Fault Behaviour Within Large Telephony Networks -- Closed Set Based Discovery of Representative Association Rules -- Intelligent Sensor Analysis and Actuator Control -- Sampling of Highly Correlated Data for Polynomial Regression and Model Discovery -- The IDA’01 Robot Data Challenge -- The IDA’01 Robot Data Challenge. | |
650 | 0 | _aDatabase management. | |
650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aComputer science. | |
650 | 0 | _aInformation storage and retrieval systems. | |
650 | 0 |
_aComputer science _xMathematics. |
|
650 | 0 | _aMathematical statistics. | |
650 | 0 | _aPattern recognition systems. | |
650 | 1 | 4 | _aDatabase Management. |
650 | 2 | 4 | _aArtificial Intelligence. |
650 | 2 | 4 | _aTheory of Computation. |
650 | 2 | 4 | _aInformation Storage and Retrieval. |
650 | 2 | 4 | _aProbability and Statistics in Computer Science. |
650 | 2 | 4 | _aAutomated Pattern Recognition. |
700 | 1 |
_aHoffmann, Frank. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aHand, David J. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aAdams, Niall M. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aFisher, Douglas. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
700 | 1 |
_aGuimaraes, Gabriela. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783540425816 |
776 | 0 | 8 |
_iPrinted edition: _z9783662211601 |
830 | 0 |
_aLecture Notes in Computer Science, _x1611-3349 ; _v2189 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/3-540-44816-0 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
912 | _aZDB-2-LNC | ||
912 | _aZDB-2-BAE | ||
942 | _cSPRINGER | ||
999 |
_c188494 _d188494 |