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AI and Financial Technology
| AI and Financial Technology |
| Autore | Giudici Paolo |
| Pubbl/distr/stampa | Frontiers Media SA, 2020 |
| Descrizione fisica | 1 electronic resource (92 p.) |
| Soggetto topico |
Science: general issues
Computer science |
| Soggetto non controllato |
FinTech
SupTech RegTech AI machine learning P2P lending Blockchain |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557669603321 |
Giudici Paolo
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| Frontiers Media SA, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Applied data mining for business and industry [[electronic resource] /] / Paolo Giudici, Silvia Figini
| Applied data mining for business and industry [[electronic resource] /] / Paolo Giudici, Silvia Figini |
| Autore | Giudici Paolo |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Hoboken, NJ, : John Wiley, 2009 |
| Descrizione fisica | 1 online resource (259 p.) |
| Disciplina |
005.74068
006.312 |
| Altri autori (Persone) | FiginiSilvia |
| Soggetto topico |
Data mining
Business - Data processing Commercial statistics |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-282-12369-6
9786612123696 0-470-05886-2 0-470-74583-5 0-470-74582-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Applied Data Mining for Business and Industry; Contents; 1 Introduction; Part I Methodology; 2 Organisation of the data; 2.1 Statistical units and statistical variables; 2.2 Data matrices and their transformations; 2.3 Complex data structures; 2.4 Summary; 3 Summary statistics; 3.1 Univariate exploratory analysis; 3.1.1 Measures of location; 3.1.2 Measures of variability; 3.1.3 Measures of heterogeneity; 3.1.4 Measures of concentration; 3.1.5 Measures of asymmetry; 3.1.6 Measures of kurtosis; 3.2 Bivariate exploratory analysis of quantitative data
3.3 Multivariate exploratory analysis of quantitative data3.4 Multivariate exploratory analysis of qualitative data; 3.4.1 Independence and association; 3.4.2 Distance measures; 3.4.3 Dependency measures; 3.4.4 Model-based measures; 3.5 Reduction of dimensionality; 3.5.1 Interpretation of the principal components; 3.6 Further reading; 4 Model specification; 4.1 Measures of distance; 4.1.1 Euclidean distance; 4.1.2 Similarity measures; 4.1.3 Multidimensional scaling; 4.2 Cluster analysis; 4.2.1 Hierarchical methods; 4.2.2 Evaluation of hierarchical methods; 4.2.3 Non-hierarchical methods 4.3 Linear regression4.3.1 Bivariate linear regression; 4.3.2 Properties of the residuals; 4.3.3 Goodness of fit; 4.3.4 Multiple linear regression; 4.4 Logistic regression; 4.4.1 Interpretation of logistic regression; 4.4.2 Discriminant analysis; 4.5 Tree models; 4.5.1 Division criteria; 4.5.2 Pruning; 4.6 Neural networks; 4.6.1 Architecture of a neural network; 4.6.2 The multilayer perceptron; 4.6.3 Kohonen networks; 4.7 Nearest-neighbour models; 4.8 Local models; 4.8.1 Association rules; 4.8.2 Retrieval by content; 4.9 Uncertainty measures and inference; 4.9.1 Probability 4.9.2 Statistical models4.9.3 Statistical inference; 4.10 Non-parametric modelling; 4.11 The normal linear model; 4.11.1 Main inferential results; 4.12 Generalised linear models; 4.12.1 The exponential family; 4.12.2 Definition of generalised linear models; 4.12.3 The logistic regression model; 4.13 Log-linear models; 4.13.1 Construction of a log-linear model; 4.13.2 Interpretation of a log-linear model; 4.13.3 Graphical log-linear models; 4.13.4 Log-linear model comparison; 4.14 Graphical models; 4.14.1 Symmetric graphical models; 4.14.2 Recursive graphical models 4.14.3 Graphical models and neural networks4.15 Survival analysis models; 4.16 Further reading; 5 Model evaluation; 5.1 Criteria based on statistical tests; 5.1.1 Distance between statistical models; 5.1.2 Discrepancy of a statistical model; 5.1.3 Kullback-Leibler discrepancy; 5.2 Criteria based on scoring functions; 5.3 Bayesian criteria; 5.4 Computational criteria; 5.5 Criteria based on loss functions; 5.6 Further reading; Part II Business case studies; 6 Describing website visitors; 6.1 Objectives of the analysis; 6.2 Description of the data; 6.3 Exploratory analysis; 6.4 Model building 6.4.1 Cluster analysis |
| Record Nr. | UNINA-9910146147203321 |
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Giudici Paolo
|
||
| Hoboken, NJ, : John Wiley, 2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Applied data mining for business and industry [[electronic resource] /] / Paolo Giudici, Silvia Figini
| Applied data mining for business and industry [[electronic resource] /] / Paolo Giudici, Silvia Figini |
| Autore | Giudici Paolo |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Hoboken, NJ, : John Wiley, 2009 |
| Descrizione fisica | 1 online resource (259 p.) |
| Disciplina |
005.74068
006.312 |
| Altri autori (Persone) | FiginiSilvia |
| Soggetto topico |
Data mining
Business - Data processing Commercial statistics |
| ISBN |
1-282-12369-6
9786612123696 0-470-05886-2 0-470-74583-5 0-470-74582-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Applied Data Mining for Business and Industry; Contents; 1 Introduction; Part I Methodology; 2 Organisation of the data; 2.1 Statistical units and statistical variables; 2.2 Data matrices and their transformations; 2.3 Complex data structures; 2.4 Summary; 3 Summary statistics; 3.1 Univariate exploratory analysis; 3.1.1 Measures of location; 3.1.2 Measures of variability; 3.1.3 Measures of heterogeneity; 3.1.4 Measures of concentration; 3.1.5 Measures of asymmetry; 3.1.6 Measures of kurtosis; 3.2 Bivariate exploratory analysis of quantitative data
3.3 Multivariate exploratory analysis of quantitative data3.4 Multivariate exploratory analysis of qualitative data; 3.4.1 Independence and association; 3.4.2 Distance measures; 3.4.3 Dependency measures; 3.4.4 Model-based measures; 3.5 Reduction of dimensionality; 3.5.1 Interpretation of the principal components; 3.6 Further reading; 4 Model specification; 4.1 Measures of distance; 4.1.1 Euclidean distance; 4.1.2 Similarity measures; 4.1.3 Multidimensional scaling; 4.2 Cluster analysis; 4.2.1 Hierarchical methods; 4.2.2 Evaluation of hierarchical methods; 4.2.3 Non-hierarchical methods 4.3 Linear regression4.3.1 Bivariate linear regression; 4.3.2 Properties of the residuals; 4.3.3 Goodness of fit; 4.3.4 Multiple linear regression; 4.4 Logistic regression; 4.4.1 Interpretation of logistic regression; 4.4.2 Discriminant analysis; 4.5 Tree models; 4.5.1 Division criteria; 4.5.2 Pruning; 4.6 Neural networks; 4.6.1 Architecture of a neural network; 4.6.2 The multilayer perceptron; 4.6.3 Kohonen networks; 4.7 Nearest-neighbour models; 4.8 Local models; 4.8.1 Association rules; 4.8.2 Retrieval by content; 4.9 Uncertainty measures and inference; 4.9.1 Probability 4.9.2 Statistical models4.9.3 Statistical inference; 4.10 Non-parametric modelling; 4.11 The normal linear model; 4.11.1 Main inferential results; 4.12 Generalised linear models; 4.12.1 The exponential family; 4.12.2 Definition of generalised linear models; 4.12.3 The logistic regression model; 4.13 Log-linear models; 4.13.1 Construction of a log-linear model; 4.13.2 Interpretation of a log-linear model; 4.13.3 Graphical log-linear models; 4.13.4 Log-linear model comparison; 4.14 Graphical models; 4.14.1 Symmetric graphical models; 4.14.2 Recursive graphical models 4.14.3 Graphical models and neural networks4.15 Survival analysis models; 4.16 Further reading; 5 Model evaluation; 5.1 Criteria based on statistical tests; 5.1.1 Distance between statistical models; 5.1.2 Discrepancy of a statistical model; 5.1.3 Kullback-Leibler discrepancy; 5.2 Criteria based on scoring functions; 5.3 Bayesian criteria; 5.4 Computational criteria; 5.5 Criteria based on loss functions; 5.6 Further reading; Part II Business case studies; 6 Describing website visitors; 6.1 Objectives of the analysis; 6.2 Description of the data; 6.3 Exploratory analysis; 6.4 Model building 6.4.1 Cluster analysis |
| Record Nr. | UNINA-9910830379703321 |
|
Giudici Paolo
|
||
| Hoboken, NJ, : John Wiley, 2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Balsamic Vinegars : Tradition, Technology, Trade / / by Paolo Giudici, Federico Lemmetti, Stefano Mazza
| Balsamic Vinegars : Tradition, Technology, Trade / / by Paolo Giudici, Federico Lemmetti, Stefano Mazza |
| Autore | Giudici Paolo |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (173 p.) |
| Disciplina | 664.55 |
| Soggetto topico |
Food—Biotechnology
Microbiology Food Science Applied Microbiology |
| ISBN | 3-319-13758-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Vinegar: definition, diffusion and use -- History of balsamic vinegars -- The balsamic family.-Balsamic production: raw materials and processes -- Traditional Balsamic: Vinegar as coded by us -- The ageing of balsamics: residence time, maturity, and yield -- Sensorial properties and evaluation of balsamic vinegars -- "Balsamic": a global debate. |
| Record Nr. | UNINA-9910298625303321 |
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Giudici Paolo
|
||
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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