Screen LibraryTowards advanced data analysis by combining soft computing and statistics /
Soft computing, as an engineering science, and statistics, as a classical branch of mathematics, emphasize different aspects of data analysis.Soft computing focuses on obtaining working solutions quickly, accepting approximations and unconventional approaches. Its strength lies in its flexibility to...
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| Corporate Authors: | |
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| Group Author: | |
| Published: |
Springer,
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| Publisher Address: | Berlin ; New York : |
| Publication Dates: | 2013. |
| Literature type: | eBook |
| Language: | English |
| Series: |
Studies in fuzziness and soft computing,
285 |
| Subjects: | |
| Online Access: |
http://dx.doi.org/10.1007/978-3-642-30278-7 |
| Summary: |
Soft computing, as an engineering science, and statistics, as a classical branch of mathematics, emphasize different aspects of data analysis.Soft computing focuses on obtaining working solutions quickly, accepting approximations and unconventional approaches. Its strength lies in its flexibility to create models that suit the needs arising in applications. In addition, it emphasizes the need for intuitive and interpretable models, which are tolerant to imprecision and uncertainty.Statistics is more rigorous and focuses on establishing objective conclusions based on experimental data by analyzing the possible situations and their (relative) likelihood. It emphasizes the need for mathematical methods and tools to assess solutions and guarantee performance.Combining the two fields enhances the robustness and generalizability of data analysis methods, while preserving the flexibility to solve real-world problems efficiently and intuitively. |
| Carrier Form: | 1 online resource. |
| Bibliography: | Includes bibliographical references and author index. |
| ISBN: |
9783642302787 (electronic bk.) 3642302785 (electronic bk.) |
| Index Number: | QA276 |
| CLC: | O212 |
| Contents: |
Arithmetic and Distance-Based Approach to the Statistical Analysis of Imprecisely Valued Data / Linear Regression Analysis for Interval-valued Data Based on Set Arithmetic: A Review / Bootstrap Confidence Intervals for the Parameters of a Linear Regression Model with Fuzzy Random Variables / On the Estimation of the Regression Model M for Interval Data / Hybrid Least-Squares Regression Modelling Using Confidence Bounds / Testing the Variability of Interval Data: An Application to Tidal Fluctuation / Comparing the Medians of a Random Interval Defined by Means of Two Different L1 Metrics / Comparing the Representativeness of the 1-norm Median for Likert and Free-response Fuzzy Scales / Fuzzy Probability Distributions in Reliability Analysis, Fuzzy HPD-regions, and Fuzzy Predictive Distributions / SAFD -- An R Package for Statistical Analysis of Fuzzy Data / Statistical Reasoning with Set-Valued Information: Ontic vs. Epistemic Views / Pricing of Catastrophe Bond in Fuzzy Framework / Convergence of Heuristic-based Estimators of the GARCH Model / Lasso-type and Heuristic Strategies in Model Selection and Forecasting / Streaming-Data Selection for Gaussian-Process Modelling / Change Detection Based on the Distribution of p-Values / Advanced Analysis of Dynamic Graphs in Social and Neural Networks / Fuzzy Hyperinference-Based Pattern Recognition / Dynamic Data-Driven Fuzzy Modeling of Software Reliability Growth / Dynamic Texture Recognition Based on Compression Artifacts / The Hubness Phenomenon: Fact or Artifact? / Proximity-Based Reference Resolution to Improve Text Retrieval / Derivation of Linguistic Summaries is Inherently Difficult: Can Association Rule Mining Help? / Mining Local Connectivity Patterns in fMRI Data / Fuzzy Clustering based on Coverings / Decision and Regression Trees in the Context of Attributes with Different Granularity Levels / Stochastic Convergence Analysis of Metaheuristic Optimisation Techniques / Comparison of Multi-objective Algorithms Applied to Feature Selection / |