1,721,030 research outputs found
Extracting Information in a Transshipment Container Terminal Data Set: an Interaction between Graphical Tools and Statistical Models
No full textFeature-Selective Oblique Trees for Regression: Application to STEM Graduate Wage Prediction in Italy
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From the Field to the Lab. An Experiment on the Representativeness of Standard Laboratory Subjects
No full textWe replicate in the laboratory an artefactual field experiment originally designed to investigate the incidence of various forms of social preferences in a representative sample of the population. Results show that, on aggregate, the two groups display a similar directional pattern in a set of simple dictator games. However, in situations in which giving is costly (or rewarding) for the dictator, the proportion of laboratory subjects who follow their self-interest is relatively higher than that in the rest of the population. We note a higher sensitivity of students, both from the laboratory and the field, to the possibility of losing part of their own payoff. Furthermore, students from the lab (all economics majors) are more sensitive to gains than students from different backgrounds even when these gains go against equality
Application of machine learning models to discriminate tourist landscapes using eye-tracking data
No full textOverlapping coefficient in network-based semi-supervised clustering
Full text linkNetwork-based Semi-Supervised Clustering (NeSSC) is a semi-supervised approach for clustering in the presence of an outcome variable. It uses a classification or regression model on resampled versions of the original data to produce a proximity matrix that indicates the magnitude of the similarity between pairs of observations measured with respect to the outcome. This matrix is transformed into a complex network on which a community detection algorithm is applied to search for underlying community structures which is a partition of the instances into highly homogeneous clusters to be evaluated in terms of the outcome. In this paper, we focus on the case the outcome variable to be used in NeSSC is numeric and propose an alternative selection criterion of the optimal partition based on a measure of overlapping between density curves as well as a penalization criterion which takes accounts for the number of clusters in a candidate partition. Next, we consider the performance of the proposed method for some artificial datasets and for 20 different real datasets and compare NeSSC with the other three popular methods of semi-supervised clustering with a numeric outcome. Results show that NeSSC with the overlapping criterion works particularly well when a reduced number of clusters are scattered localized
Topic based quality indexes assessment through sentiment
Full text linkThis paper proposes a new methodology called TOpic modeling Based Index Assessment through Sentiment (TOBIAS). This method aims at modeling the effects of the topics, moods, and sentiments of the comments describing a phenomenon upon its overall rating. TOBIAS is built combining different techniques and methodologies. Firstly, Sentiment Analysis identifies sentiments, emotions, and moods, and Topic Modeling finds the main relevant topics inside comments. Then, Partial Least Square Path Modeling estimates how they affect an overall rating that summarizes the performance of the analyzed phenomenon. We carried out TOBIAS on a real case study on the university courses’ quality evaluated by the University of Cagliari (Italy) students. We found TOBIAS able to provide interpretable results on the impact of discussed topics by students with their expressed sentiments, emotions, and moods and with the overall rating
Improving the performance of image segmentation methods through background subtraction
No full textMany image segmentation algorithms have been proposed to partition an image into foreground regions of interest and background regions to be ignored. These algorithms use pixel intensities to partition the image, so it should be good practice to choose an appropriate background color as different as possible from foreground one. In the case of a unique digitizing operation the user can make the choice of background color by himself in order to obtain a good result in segmentation process, but in the case of several digitizing operations it would be useful to automate the whole process by removing any decision of the user about the choice of background color. Furthermore modern instruments allow capturing images with a high resolution characterized by a massive number of pixels, and pose speed problems to image segmentation algorithms ased on a local thresholding approach. In this work an approach that adapt a widely used method for detecting moving objects from a video, called background subtraction, is introduced to the image segmentation framework characterized by the specific situation in which background of the image is changeable. Respect to the standard methods, it adds new information into segmentation process. A comparison between standard
methods and the approach proposed has been presented, applying both a Global and a Local thresholding method. The background subtraction approach proposed allows to improve quality of segmentation output, to automatize the process when foreground color of images is not homogeneous, and to speed it up
Comparison of Cluster Analysis Approaches for Binary Data
No full textCluster methods allow to partition observations into homogeneous groups. Standard cluster analysis approaches consider the variables used to partition observations as continuous. In this work, we deal with the particular case all variables are binary. We focused on two specific methods that can handle binary data: the monothetic analysis and the model-based co-clustering. The aim is to compare the outputs performing these two methods on a common dataset, and figure out how they differ. The dataset on which the two methods are performed is a UNESCO dataset made up of 58 binary variables concerning the ability of UNESCO management to use Internet to promote world heritage sites
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