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Advanced R statistical programming and data models : analysis, machine learning, and visualization / / by Matt Wiley, Joshua F. Wiley
| Advanced R statistical programming and data models : analysis, machine learning, and visualization / / by Matt Wiley, Joshua F. Wiley |
| Autore | Wiley Matt |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Berkeley, CA : , : Apress : , : Imprint : Apress, , 2019 |
| Descrizione fisica | 1 online resource (XX, 638 p. 207 illus., 127 illus. in color.) |
| Disciplina | 005.13 |
| Soggetto topico |
R (Llenguatge de programació)
Estadística matemàtica Programming languages (Electronic computers) Computer programming Mathematical statistics R (Computer program language) Programming Languages, Compilers, Interpreters Programming Techniques Probability and Statistics in Computer Science |
| ISBN |
9781523150311
1523150319 9781484228722 1484228723 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1 Univariate Data Visualization -- 2 Multivariate Data Visualization -- 3 Generalized Linear Models 1 -- 4 Generalized Linear Models 2 -- 5 Generalized Additive Models -- 6 Machine Learning: Introduction -- 7 Machine Learning: Unsupervised -- 8 Machine Learning: Supervised -- 9 Missing Data -- 10 Generalized Linear Mixed Models: Introduction -- 11 Generalized Linear Mixed Models: Linear -- 12 Generalized Linear Mixed Models: Advanced -- 13 Modeling IIV -- Bibliography. |
| Record Nr. | UNINA-9910338002703321 |
Wiley Matt
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| Berkeley, CA : , : Apress : , : Imprint : Apress, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances and Innovations in Statistics and Data Science [[electronic resource] /] / edited by Wenqing He, Liqun Wang, Jiahua Chen, Chunfang Devon Lin
| Advances and Innovations in Statistics and Data Science [[electronic resource] /] / edited by Wenqing He, Liqun Wang, Jiahua Chen, Chunfang Devon Lin |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (338 pages) |
| Disciplina | 519.5 |
| Collana | ICSA Book Series in Statistics |
| Soggetto topico |
Biometry
Statistics Artificial intelligence - Data processing Machine learning Biostatistics Applied Statistics Data Science Machine Learning Estadística matemàtica Processament de dades |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-031-08329-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. MiRNA-Gene Activity Interaction Networks (miGAIn): Integrated joint models of miRNA-gene targeting and disturbance in signal processing -- 2. Feature Screening for Ultrahigh-Dimensional Regression with Error-Prone Varables -- 3. Cosine Distribution in the Post-selection Inference of Least Angle Regression -- 4. Learning Finite Gaussian Mixture via Wasserstein Distance -- 5. An Entropy-based Method with Word Embedding Clustering for Comment Ranking -- 6. Estimation in Functional Linear Model with Incomplete Functional Observations -- 7. A Flexible Linear Single Index Proportional Hazards Regression Model for Multivariate Survival Data -- 8. Efficient Estimation of Semiparametric Linear Transformation Model with Left-Truncated and Current Status Data -- 9. Flexible Transformations for Modeling Compositional Data -- 10. Identifiability and Estimation of Autoregressive ARCH Models with Measurement Error -- 11. Modal Regression for Skewed, Truncated, or Contaminated Data with Outliers -- 12. Spatial Multilevel Modeling in the Galveston Bay Recovery Study Survey -- 13. Efficient Experimental Design for Regularized Linear Models -- 14. A Selective Overview of Statistical Models for Identification of Treatment-sensitive Subset -- 15. Analysis of Discrete Compositional Series While Accounting for Informative Time-dependent Cluster Sizes with Application to Air Pollution Related Emergency Room Visits. |
| Record Nr. | UNISA-996495167803316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Advances and Innovations in Statistics and Data Science / / edited by Wenqing He, Liqun Wang, Jiahua Chen, Chunfang Devon Lin
| Advances and Innovations in Statistics and Data Science / / edited by Wenqing He, Liqun Wang, Jiahua Chen, Chunfang Devon Lin |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (338 pages) |
| Disciplina |
519.5
001.422 |
| Collana | ICSA Book Series in Statistics |
| Soggetto topico |
Biometry
Statistics Artificial intelligence - Data processing Machine learning Biostatistics Applied Statistics Data Science Machine Learning Estadística matemàtica Processament de dades |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-031-08329-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. MiRNA-Gene Activity Interaction Networks (miGAIn): Integrated joint models of miRNA-gene targeting and disturbance in signal processing -- 2. Feature Screening for Ultrahigh-Dimensional Regression with Error-Prone Varables -- 3. Cosine Distribution in the Post-selection Inference of Least Angle Regression -- 4. Learning Finite Gaussian Mixture via Wasserstein Distance -- 5. An Entropy-based Method with Word Embedding Clustering for Comment Ranking -- 6. Estimation in Functional Linear Model with Incomplete Functional Observations -- 7. A Flexible Linear Single Index Proportional Hazards Regression Model for Multivariate Survival Data -- 8. Efficient Estimation of Semiparametric Linear Transformation Model with Left-Truncated and Current Status Data -- 9. Flexible Transformations for Modeling Compositional Data -- 10. Identifiability and Estimation of Autoregressive ARCH Models with Measurement Error -- 11. Modal Regression for Skewed, Truncated, or Contaminated Data with Outliers -- 12. Spatial Multilevel Modeling in the Galveston Bay Recovery Study Survey -- 13. Efficient Experimental Design for Regularized Linear Models -- 14. A Selective Overview of Statistical Models for Identification of Treatment-sensitive Subset -- 15. Analysis of Discrete Compositional Series While Accounting for Informative Time-dependent Cluster Sizes with Application to Air Pollution Related Emergency Room Visits. |
| Record Nr. | UNINA-9910624380703321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in compositional data analysis : festschrift in honour of Vera Pawlowsky-Glahn / / Peter Filzmoser, Karel Hron, Josep Antoni Martín-Fernández, Javier Palarea-Albaladejo, editors
| Advances in compositional data analysis : festschrift in honour of Vera Pawlowsky-Glahn / / Peter Filzmoser, Karel Hron, Josep Antoni Martín-Fernández, Javier Palarea-Albaladejo, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XVIII, 404 p. 113 illus., 91 illus. in color.) |
| Disciplina | 519.5 |
| Altri autori (Persone) | Pawlowsky-GlahnVera |
| Soggetto topico |
Estadística matemàtica
Investigació quantitativa Mathematical statistics Quantitative research |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-71175-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- J.J. Egozcue and W.L. Maldonado: An interpretable orthogonal decomposition of positive square matrices -- Part I Fundamentals -- I. Erb and N. Ay: The information-geometric perspective of compositional data analysis -- D.R. Lovell: Log-ratio analysis of finite precision data: caveats, and connections to digital lines and number theory -- G. Mateu-Figueras, G.S. Monti and J.J. Egozcue: Distributions on the simplex revisited -- J. Graffelman: Compositional biplots: a story of false leads and hidden features revealed by the last dimensions -- Part II Statistical Methodology -- K. Fačevicová, P. Kynčlová and K. Macků: Geographically weighted regression analysis for two-factorial compositional data -- C. Barceló-Vidal and J.A. Martín-Fernández: Factor analysis of compositional data with a total -- M. Gallo, V. Simonacci and V. Todorov: A compositional three-way approach for student satisfaction analysis -- M. Templ: Artificial neural networks to impute rounded zeros in compositional data -- E. Saus–Sala, À. Farreras–Noguer, N. Arimany–Serrat, and G. Coenders: Compositional du pont analysis. A visual tool for strategic financial performance assessment -- A. Menafoglio: Spatial statistics for distributional data in Bayes spaces: from object-oriented kriging to the analysis of warping functions -- C. Thomas-Agnan, T. Laurent, A. Ruiz-Gazen, N. Thi Huong An, R. Chakir and A. Lungarska: Spatial simultaneous autoregressive models for compositional data: application to land use -- Part III Applications -- A. Buccianti, C. Gozzi: The whole versus the parts: the challenge of compositional data analysis (CoDA) methods for geochemistry -- M.A. Engle and J.A. Chaput: Groundwater origin determination in historic chemical datasets through supervised compositional data analysis: Brines of the Permian Basin, USA -- J.M. McKinley, U. Mueller, P.M. Atkinson, U. Ofterdinger, S.F. Cox, R. Doherty, D. Fogarty and J.J. Egozcue -- Chronic kidney disease of uncertain aetiology and its relation with waterborne environmental toxins: An investigation via compositional balances -- R.A. Olea, J.A. Martín-Fernández and W.H. Craddock: Multivariate classification of the crude oil petroleum systems in southeast Texas, USA, using conventional and compositional data analysis of biomarkers -- J.R. Wu, J.M. Macklaim, B.L. Genge and G.B. Gloor: Finding the centre: compositional asymmetry in high-throughput sequencing datasets -- L. Huang and H. Li: Bayesian balance-regression in microbiome studies using stochastic search -- D.E. McGregor, P.M. Dall, J. Palarea-Albaladejo and S.F.M. Chastin: Compositional data analysis in physical activity and health research. Looking for the right balance -- D. Dumuid, Ž. Pedišić, J. Palarea-Albaladejo, J.A. Martín-Fernández, K. Hron and T. Olds: Compositional data analysis in time-use epidemiology. |
| Record Nr. | UNISA-996466397003316 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Advances in data analysis and classification
| Advances in data analysis and classification |
| Pubbl/distr/stampa | Berlin, : Springer |
| Soggetto topico |
Mathematical statistics
Classification Estadística matemàtica |
| Soggetto genere / forma |
Internet resource
Periodicals. Revistes electròniques. |
| ISSN | 1862-5355 |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | ADAC |
| Record Nr. | UNINA-9910144885903321 |
| Berlin, : Springer | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in data science / / Ilke Demir [and three others], editors
| Advances in data science / / Ilke Demir [and three others], editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer International Publishing, , [2021] |
| Descrizione fisica | 1 online resource (374 pages) |
| Disciplina | 515.63 |
| Collana | Association for Women in Mathematics |
| Soggetto topico |
Calculus of tensors - Data processing
Estadística matemàtica Càlcul de tensors Informàtica Calculus of tensors |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-030-79891-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996466413703316 |
| Cham, Switzerland : , : Springer International Publishing, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in data science / / Ilke Demir [and three others], editors
| Advances in data science / / Ilke Demir [and three others], editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer International Publishing, , [2021] |
| Descrizione fisica | 1 online resource (374 pages) |
| Disciplina | 515.63 |
| Collana | Association for Women in Mathematics |
| Soggetto topico |
Calculus of tensors - Data processing
Estadística matemàtica Càlcul de tensors Informàtica Calculus of tensors |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-030-79891-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910512174003321 |
| Cham, Switzerland : , : Springer International Publishing, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in Intelligent Data Analysis XXII : 22nd International Symposium on Intelligent Data Analysis, IDA 2024, Stockholm, Sweden, April 24–26, 2024, Proceedings, Part I / / edited by Ioanna Miliou, Nico Piatkowski, Panagiotis Papapetrou
| Advances in Intelligent Data Analysis XXII : 22nd International Symposium on Intelligent Data Analysis, IDA 2024, Stockholm, Sweden, April 24–26, 2024, Proceedings, Part I / / edited by Ioanna Miliou, Nico Piatkowski, Panagiotis Papapetrou |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (XVI, 268 p. 74 illus., 61 illus. in color.) |
| Disciplina | 005.7 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Database management
Education - Data processing Image processing - Digital techniques Computer vision Artificial intelligence Machine learning Natural language processing (Computer science) Database Management System Computers and Education Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence Machine Learning Natural Language Processing (NLP) Reconeixement de formes (Informàtica) Estadística matemàtica Processament de dades |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN |
9783031585470
303158547X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Foundations of AI and ML -- Tackling the Abstraction and Reasoning Corpus (ARC) with Object-Centric Models and the MDL Principle -- 1 Introduction -- 2 Related Work -- 3 Object-Centric Models -- 3.1 Mixing Patterns and Functions -- 3.2 Parsing and Generating Grids with a Grid Model -- 3.3 Predict and Describe Grids with Task Models -- 4 MDL-Based Model Learning -- 4.1 Description Lengths -- 4.2 Search Space and Strategy -- 4.3 Pruning Phase -- 5 Evaluation -- 6 Conclusion -- References -- RMI-RRG: A Soft Protocol to Postulate Monotonicity Constraints for Tabular Datasets -- 1 Introduction -- 2 Related Work -- 3 Preliminaries and Notation -- 3.1 Rank Mutual Information -- 3.2 Relabeling -- 4 Main Direct Competitors -- 4.1 Subjective Approaches -- 4.2 Objective Approaches -- 5 RMI Tables and Required Relabelings Graphs -- 6 The RMI-RRG Protocol -- 7 Experimental Results -- 7.1 Breast Cancer -- 7.2 Car -- 7.3 CMC -- 7.4 Pasture -- 7.5 PIMA -- 7.6 Windsor -- 8 Conclusions -- References -- A Structural-Clustering Based Active Learning for Graph Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation -- 3.1 Node Classification on Attributed Graphs -- 3.2 Graph Neural Networks (GNNs) -- 3.3 Active Learning Task for Graph Neural Networks -- 4 Proposed Method -- 4.1 Community Detection Using the SCAN Algorithm -- 4.2 Node Selection Based on PageRank -- 4.3 SPA Algorithm -- 5 Experiments -- 5.1 Experiment Settings -- 5.2 Dataset -- 5.3 Evaluation Metrics -- 5.4 Baselines Methods -- 6 Results -- 6.1 Experiment Results of SPA on GCN -- 6.2 Experiment Result of SPA on GraphSAGE -- 6.3 Complexity Analysis -- 7 Discussion and Conclusion -- References -- Multi-armed Bandits with Generalized Temporally-Partitioned Rewards -- 1 Introduction.
2 Background and Related Work -- 3 Problem Formulation -- 4 Lower Bound on Regret -- 5 Proposed Algorithm and Regret Upper Bound -- 5.1 Proposed Algorithm: TP-UCB-FR-G -- 5.2 Regret Upper Bound of TP-UCB-FR-G -- 6 Experimental Results -- 6.1 Setting 1: Synthetic Environment -- 6.2 Setting 2: Spotify Playlists -- 7 Concluding Remarks and Future Work -- References -- GloNets: Globally Connected Neural Networks -- 1 Introduction -- 2 Notation and Model Definition -- 3 Related Work -- 4 Implementing GloNet -- 5 Experiments -- 6 Conclusions and Future Works -- References -- Mind the Data, Measuring the Performance Gap Between Tree Ensembles and Deep Learning on Tabular Data -- 1 Introduction -- 2 Preliminaries -- 2.1 Tabular Data -- 2.2 Tree Ensembles -- 2.3 Deep Learning -- 3 Related Work -- 4 Methodology and Design of Experiments -- 5 Results -- 5.1 Impact of Training Dataset Size -- 5.2 Feature Complexity -- 5.3 Explainability -- 6 Conclusions and Future Work -- References -- A Remark on Concept Drift for Dependent Data -- 1 Introduction -- 2 Problem Setup -- 2.1 A Probability Theoretical Framework for Concept Drift -- 2.2 Stochastic Processes -- 2.3 A Taxonomy of Change Detection in Data Streams -- 3 Consistency Property -- 3.1 Drift is not Non-Stationarity -- 3.2 Temporal Consistency -- 3.3 Measuring Consistency of a Noisy Stochastic Processes -- 4 Numerical Evaluation -- 4.1 Testing Stationarity -- 4.2 Evaluation of Method -- 5 Conclusion -- References -- Representation Learning -- Variational Perspective on Fair Edge Prediction -- 1 Introduction -- 2 Related Work -- 3 Variational Fairness-Aware Node Embedding -- 3.1 Problem Set-Up -- 3.2 Definition of the Loss -- 3.3 Optimization of LEAVE -- 4 Experiments and Results -- 4.1 Edge Prediction Protocol -- 4.2 Evaluation Metrics -- 4.3 Baselines for Edge Prediction -- 4.4 Analysis of Results. 5 Conclusion -- References -- Node Classification in Random Trees -- 1 Introduction -- 2 Related Work -- 2.1 Learning Probabilistic Graphical Models -- 2.2 Node Classification Using Graph Neural Networks -- 3 Method -- 3.1 Problem Formulation -- 3.2 Approach -- 3.3 GNN Design -- 3.4 Classifying Nodes -- 4 Evaluation -- 4.1 Dataset -- 4.2 Experiments -- 4.3 Results -- 5 Conclusion -- References -- Self-supervised Siamese Autoencoders -- 1 Introduction -- 2 Self-supervised Representation Learning -- 3 A Siamese Denoising Autoencoder -- 3.1 Motivation -- 3.2 Architecture -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Results -- 5 Related Work -- 6 Conclusion -- References -- Equivariant Parameter Sharing for Porous Crystalline Materials -- 1 Introduction -- 2 Related Work -- 3 Crystal Symmetries -- 4 Methods -- 5 Experiments -- 6 Discussion -- References -- Subgraph Mining for Graph Neural Networks -- 1 Introduction -- 2 Preliminaries -- 3 AutoGSN -- 3.1 Subgraph Mining -- 3.2 Selection -- 3.3 Counting -- 4 Experiments -- 5 Related Work -- 6 Conclusion -- References -- Applications -- Super-Resolution Analysis for Landfill Waste Classification -- 1 Introduction -- 2 Related Work -- 2.1 Image Classification for Landfills Discovery -- 2.2 Image Quality Improvement -- 3 Methodology -- 3.1 Experimental Setup -- 3.2 Results -- 4 Conclusions -- References -- Predicting Performance Drift in AI Models of Healthcare Without Ground Truth Labels -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Probabilistic Sources of Drift -- 3.2 Drift Detection Framework -- 4 Results -- 4.1 Simulated Data -- 4.2 UK Primary Care Covid-19 Data -- 5 Conclusions -- References -- An Interpretable Human-in-the-Loop Process to Improve Medical Image Classification -- 1 Introduction -- 2 Methodology -- 2.1 Dataset Description -- 2.2 Baseline Classifier Description. 2.3 Concept-Based Interpretability -- 2.4 Concept Selection -- 2.5 Human-in-the-Loop Approach -- 3 Results and Discussion -- 3.1 Baseline Classifiers -- 3.2 Concept-Based Interpretability Results -- 3.3 Human-in-the-Loop Approach Results -- 4 Conclusion -- References -- Hybrid Ensemble-Based Travel Mode Prediction -- 1 Introduction -- 2 Related Works -- 3 Ensemble of Batch and Online Learners -- 3.1 Training of Online and Batch Learners with TMC Data Streams -- 3.2 Building an Ensemble of Batch and Online Learners -- 4 Results -- 4.1 Data Streams and Libraries -- 4.2 Experiments -- 4.3 Discussion -- 5 Conclusions -- References -- Natural Language Processing -- Beyond Words: A Comparative Analysis of LLM Embeddings for Effective Clustering -- 1 Introduction -- 2 Related Work -- 3 Models and Algorithms -- 3.1 Clustering Algorithms -- 4 Numerical Experiments -- 4.1 Evaluation Metrics -- 4.2 Experimental Settings -- 4.3 Results and Discussion -- 5 Conclusion and Perspectives -- References -- Data Quality in NLP: Metrics and a Comprehensive Taxonomy -- 1 Introduction -- 1.1 Data Quality -- 2 Related Work -- 3 Taxonomy for Data Quality in NLP -- 3.1 Linguistic -- 3.2 Semantic -- 3.3 Anomaly -- 3.4 Classifier Performance -- 3.5 Diversity -- 4 Experimental Setup -- 5 Results and Discussion -- 6 Conclusion and Future Works -- References -- Building Brownian Bridges to Learn Dynamic Author Representations from Texts -- 1 Introduction -- 2 Related Works -- 3 BARL: Brownian Bridges for Author Representation Learning -- 3.1 Background -- 3.2 Using the Brownian Bridges -- 3.3 Variational Information Bottleneck -- 3.4 Learning Author Representations -- 3.5 Model Architecture of BARL -- 4 Experiments with BARL -- 4.1 Datasets -- 4.2 Parameter Settings and Competitors -- 4.3 Results in Authorship Attribution -- 4.4 Results in Document Dating. 4.5 Results in Author Classification -- 4.6 Ablation Study -- 4.7 Qualitative Analysis -- 5 Conclusion -- References -- Automatically Detecting Political Viewpoints in Norwegian Text -- 1 Introduction -- 2 Related Work -- 2.1 Political Text Analysis -- 2.2 Domain- and Language-Specific LLMs -- 2.3 Masking Techniques -- 3 The nor-pvi Dataset -- 4 Encoder-Decoder Models -- 4.1 Training Datasets -- 4.2 Setup and Training -- 5 Experiments and Evaluations -- 6 Results and Discussions -- 7 Conclusion and Future Work -- References -- AHAM: Adapt, Help, Ask, Model Harvesting LLMs for Literature Mining -- 1 Introduction -- 2 Related Work -- 3 Experimental Data: Literature-Based Discovery Publications -- 4 Methodology -- 4.1 Domain-Adaptation via Sentence-Transformers and BERTopic -- 4.2 Prompt Engineering of LLMs to Design Topic Names -- 4.3 Assessing Adaptation Through Evaluation of Topic Naming -- 4.4 AHAM Heuristic -- 5 Quantitative Exploration of the AHAM Objective -- 6 Qualitative Evaluation -- 7 Conclusion and Further Work -- References -- Author Index. |
| Record Nr. | UNINA-9910847588803321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in Machine Learning and Big Data Analytics I : ICMLBDA 2023, NIT Arunachal Pradesh, India, May 29-30 / / edited by Ashokkumar Patel, Nishtha Kesswani, Madhusudhan Mishra, Preetisudha Meher
| Advances in Machine Learning and Big Data Analytics I : ICMLBDA 2023, NIT Arunachal Pradesh, India, May 29-30 / / edited by Ashokkumar Patel, Nishtha Kesswani, Madhusudhan Mishra, Preetisudha Meher |
| Autore | Patel Ashokkumar |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (870 pages) |
| Disciplina | 005.7 |
| Altri autori (Persone) |
KesswaniNishtha
MishraMadhusudhan MeherPreetisudha |
| Collana | Springer Proceedings in Mathematics & Statistics |
| Soggetto topico |
Mathematical statistics
Machine learning Quantitative research Artificial intelligence - Data processing Mathematical Statistics Machine Learning Data Analysis and Big Data Data Science Estadística matemàtica Aprenentatge automàtic Investigació quantitativa Intel·ligència artificial Processament de dades Mineria de dades |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
9783031513381
303151338X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- Similarity Analysis of Protein Sequences with a New 3-D Graphical Representation Technique -- Enhanced Security and Robustness of Data Using Steganography -- A TTIG Based Deep Convolution Combined GAN and CLS for Text to Image Synthesis -- Smart Agricultural Greenhouse System: A Context-aware Application -- Improving Performance of Plant Disease Detection using YOLOv7 and YOLOv8 -- Detection of Congenital Heart Disease from Heart Sounds using 2DCNN-BiLSTM with Attention Mechanism -- Automated Reviewer Assignment Process using Machine Learning Technique -- A Method for Detecting Retinal Micro aneurysms in the Fundus Using CR-SF And RG-TF -- Pilot Super Resolution Network (PSRN) based Mango fruit Classification -- Performance Evaluation of Quality of Service (QoS) in Modified Ad hoc On-Demand Distance Vector (MAODV) Routing Protocol in Manets -- Minimize the Energy Consumption to Increase the Network Lifetime for Green IoT Environment -- Unveiling Hate Speech: Identifying Toxic Comments Targeting Women in Online Social Media Posts -- Identification of retinal fundus in diabetic patients using deep learning algorithms -- Smart Health Prediction Using Random Forest -- Vulnerability Assessment and Penetration Testing Using Parrot Operating System -- Assessing NSAID Threat Degree of Unfavorable Medical Reactions Using Machine Learning -- Searchable Encryption for Privacy Preserving with Fine Grained Access Control -- Classification for Disease Gene Association -- Machine Learning-Based Air Pollution Monitoring And Forecasting -- A Novel parasitic mushroom-like structure with high gain microstrip patch antenna for broadband applications -- Facial Emotion Recognition using Artificial Intelligence -- A Hybrid Machine Intelligence Demographic Feature Selection Approach to Improve Recommendation System in Social Domain -- An Exploratory Review of Machine Learning and Deep Learning Applications in Healthcare Management -- Bone Fracture Prediction using Machine Learning and Deep Learning Techniques -- Plant Disease Detection Using Modern Deep Learning Approach: YOLOv7 -- Analysis of the life insurance business performance based on COVID by using machine learning algorithms -- An Ensemble Model of Skin Disease Detection Using CNN and Transfer Learning -- Session Based News Recommendation System -- A Fusion-based Approach for Generating Image Captions -- Comparison of Machine Learning Algorithms for Detection of Stuttering in Speech -- The Evolutionary Impact of Pattern Recognition in Research Applications – A Wide Spectrum Survey -- Prediction of GATE Examination Clearance for Fresh Graduate Candidates: An Advanced Machine Learning Approach -- Foreseeing Worker Attrition Using Machine Learning -- Mouse Controlling Using Eyeball Action -- Power Quality Improvement by Using Shunt Hybrid Active Power Filter -- Integration of Renewable Energy Systems into utility grid: A review on Power Quality Issues, Mitigating devices and Control Algorithms -- Traffic Control System for Congestion Control and Ambulance Clearance -- QR Based Authentication for Login and Payment -- Smart Irrigation Watering System Using IoT -- IoT Based Transmission Line Multiple Fault Detection and Indication to Electricity Board -- Design Of Off Board Electric Vehicle Charger Using PV Array Through Matlab-Simulink -- Human stress detection in sleep mode compared with non-sleep mode using machine learning algorithms -- Medical Diagnosis Prediction using Deep Learning -- Detecting Hard Landing of Flights: E-Pilots -- Detection of Glaucoma Using MobileNet, XAI and IML -- Attainment Expedients of Markovian Heterogeneous Water Heaters in Queueing Models by Matrix Geometry Method -- Identification Of Medicinal Plants Using Inception V3 Model -- Smart Gardening Using Internet of Things -- Predictive Analytics of Blood Donor Risk Assessment Using Machine Learning Methods -- Risk Analysis of Covid-19 Patients Mortality Rate in Emergency Ward -- Machine Learning Classification Analysis on Leaf Disease Data -- Conversion of Type-2 Intuitionistic Fuzzy Sets into Interval-valued Intuitionistic Fuzzy Sets and its implementation in Decision Making -- A Framework for Secure Database and Similarity Comparison in Android -- A Comprehensive review and a Conceptual framework for predicting the position of the mobile sinks in Wireless sensor networks -- Brain Computer Interface for Multiple Applications Control -- Predicting Student Academic Performance using Machine Learning: A Comparison of Classification Algorithms -- A Novel Approach in Machine Learning for Solar Energy Prediction System -- Real-time Tomato Leaf Disease Detection and Diagnosis using Deep Learning-based Computer Vision Techniques -- Index. |
| Record Nr. | UNINA-9910983069003321 |
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Patel Ashokkumar
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in probability and mathematical statistics : CLAPEM 2019, Mérida, Mexico / / edited by Daniel Hernández‐Hernández [and three others]
| Advances in probability and mathematical statistics : CLAPEM 2019, Mérida, Mexico / / edited by Daniel Hernández‐Hernández [and three others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Birkhäuser, , [2021] |
| Descrizione fisica | 1 online resource (178 pages) |
| Disciplina | 519.5 |
| Collana | Progress in Probability |
| Soggetto topico |
Mathematical statistics
Probabilities Estadística matemàtica Probabilitats |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-030-85325-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910508450003321 |
| Cham, Switzerland : , : Birkhäuser, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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