Computational Intelligence II -- Multimodal Skin Cancer Classification Optimized Convolutional Network with Customized Loss and RNN Based FCNN Fusion -- Deep Learning Based MLP Model in Detection of Cotton Plant Leaf Disease -- Enhancing Drug Candidate Generation Comparing Genetic Algorithm And...

Computational Intelligence I -- Depression Clinic People's Mental Health Prediction Using Information from Online Social Media Networks (OSN) -- A Novel Hindi Voice Based Assistant System Architecture for E Commerce -- Early Classification of Alzheimer’s Disease Using Deep Learning Technique...

Zusammenfassung Der Beitrag schildert die Effekte partieller Antwortverweigerung auf die Ergebnisse multivariater statistischer Analysen anhand von Produktivitätsschätzungen auf Betriebsdatenebene. Als Datenbasis dient das IAB-Betriebspanel aus dem Jahr 2000, wobei fehlende Daten mit Hilfe des...

Der Beitrag schildert die Effekte von Antwortausfällen bei einzelnen Fragen („item non-response“) auf die Ergebnissevon multivariaten statistischen Analysen. Dabei wird das Verfahren der „Data Augmentation“ angewendet,um die fehlenden Daten zu ersetzen (Schafer 1997). Anhand von...

Der Beitrag schildert die Effekte von Antwortausfällen bei einzelnen Fragen ("item non-response") auf die Ergebnisse von multivariaten statistischen Analysen. Dabei wird das Verfahren der "Data Augmentation" angewendet, um die fehlenden Daten zu ersetzen (Schafer 1997). Anhand von Schätzungen...

Most macroeconomic indicators failed to capture the sharp economic fluctuations during the Corona crisis in a timely manner. Instead, alternative high-frequency data have been used, aiming to monitor the economic situation. However, these data are often only loosely related to the business cycle...

This paper provides an empirical analysis of a range of alternative single-factor continuous time models for the Australian short-term interest rate. The models are indexed by the level effect parameter for the volatility in the short rate process. The inferential approach adopted is Bayesian,...

Traditional CRM models often ignore the correlation that could exist among the purchasing behavior of surrounding prospects. Hence, a generalized linear autologistic regression model can be used to capture this interdependence and improve the predictive performance of the model. In particular,...

The purpose of this paper is to evaluate whether pictorial data can improve customer churn prediction and, if so, which pictures are most important. We use Random Forest and five times twofold cross-validation to analyze how much pictorial stimulus-choice data increase the AUC and top decile...

We propose a consumption-based capital asset pricing model in which the representative agent's preferences display state-dependent risk aversion. We obtain a valuation equation in which the vector of excess returns on equity includes both consumption risk as well as the risk associated with...