The extropy has recently been introduced as the dual concept of entropy. Moreover, in the context of the Dempster–Shafer evidence theory, Deng studied a new measure of discrimination, named the Deng ...entropy. In this paper, we define the Deng extropy and study its relation with Deng entropy, and examples are proposed in order to compare them. The behaviour of Deng extropy is studied under changes of focal elements. A characterization result is given for the maximum Deng extropy and, finally, a numerical example in pattern recognition is discussed in order to highlight the relevance of the new measure.
The aging intensity (AI), defined as the ratio of the instantaneous hazard rate and a baseline hazard rate, is a useful tool for the describing reliability properties of a random variable ...corresponding to a lifetime. In this work, the concept of AI is introduced in step-stress accelerated life testing (SSALT) experiments, providing new insights to the model and enabling the further clarification of the differences between the two commonly employed cumulative exposure (CE) and tampered failure rate (TFR) models. New AI-based estimators for the parameters of a SSALT model are proposed and compared to the MLEs in terms of examples and a simulation study.
Analyzing how BERT performs entity matching Paganelli, Matteo; Buono, Francesco Del; Baraldi, Andrea ...
Proceedings of the VLDB Endowment,
04/2022, Letnik:
15, Številka:
8
Journal Article
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State-of-the-art Entity Matching (EM) approaches rely on transformer architectures, such as
BERT
, for generating highly contex-tualized embeddings of terms. The embeddings are then used to predict ...whether pairs of entity descriptions refer to the same real-world entity. BERT-based EM models demonstrated to be effective, but act as black-boxes for the users, who have limited insight into the motivations behind their decisions.
In this paper, we perform a multi-facet analysis of the components of pre-trained and fine-tuned BERT architectures applied to an EM task. The main findings resulting from our extensive experimental evaluation are (1) the fine-tuning process applied to the EM task mainly modifies the last layers of the BERT components, but in a different way on tokens belonging to descriptions of matching / non-matching entities; (2) the special structure of the EM datasets, where records are pairs of entity descriptions is recognized by BERT; (3) the pair-wise semantic similarity of tokens is not a key knowledge exploited by BERT-based EM models.
This paper showcases Time2Feat, an end-to-end machine learning system for Multivariate Time Series (MTS) clustering. The system relies on interpretable inter-signal and intra-signal features ...extracted from the time series. Then, a dimensionality reduction technique is applied to select a subset of features that retain most of the information, thus enhancing the interpretability of the results. In addition, the system enables domain specialists to semi-supervise the process by submitting a small collection of MTS with a target cluster. This process further improves both accuracy and interpretability, by reducing the number of features used by the clustering process. The demonstration shows the application of Time2Feat to various MTS datasets, by creating clusters from MTS datasets of interest, experimenting with different settings and using the approach capabilities to interpret the clusters generated.
Time2Feat Bonifati, Angela; Buono, Francesco Del; Guerra, Francesco ...
Proceedings of the VLDB Endowment,
10/2022, Letnik:
16, Številka:
2
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Clustering multivariate time series is a critical task in many real-world applications involving multiple signals and sensors. Existing systems aim to maximize effectiveness, efficiency and ...scalability, but fail to guarantee the interpretability of the results. This hinders their application in critical real scenarios where human comprehension of algorithmic behavior is required. This paper introduces Time2Feat, an end-to-end machine learning system for multivariate time series (MTS) clustering. The system relies on inter-signal and intra-signal interpretable features extracted from the time series. Then, a dimensionality reduction technique is applied to select a subset of features that retain most of the information, thus enhancing the interpretability of the results. In addition, domain experts can semi-supervise the process, by providing a small amount of MTS with a target cluster. This process further improves both accuracy and interpretability, narrowing down the number of features used by the clustering process. We demonstrate the effectiveness, interpretability, efficiency, and robustness of Time2Feat through experiments on eighteen benchmarking time series datasets, comparing them with state-of-the-art MTS clustering methods.
Deng entropy and extropy are two measures useful in the Dempster–Shafer evidence theory (DST) to study uncertainty, following the idea that extropy is the dual concept of entropy. In this paper, we ...present their fractional versions named fractional Deng entropy and extropy and compare them to other measures in the framework of DST. Here, we study the maximum for both of them and give several examples. Finally, we analyze a problem of classification in pattern recognition in order to highlight the importance of these new measures.
In June 2022, at the XXXII Conference of the Italian Society of Parasitology, the parallels of the main endoparasitic infections of horses and donkeys were discussed. Although these 2 species are ...genetically different, they can be challenged by a similar range of parasites (i.e. small and large strongyles, and Parascaris spp.). Although equids can demonstrate some level of resilience to parasites, they have quite distinct helminth biodiversity, distribution and intensity among different geographical locations and breeds. Heavily infected donkeys may show fewer clinical signs than horses. Although parasite control is primarily provided to horses, we consider that there may be a risk of drug-resistance parasitic infection through passive infection in donkeys when sharing the same pasture areas. Knowing the possible lack of drug efficacy (<90 or 80%), it is advocated the use of selective treatment for both species based on fecal egg counts. Adult horses should receive treatment when the threshold exceeds 200–500 eggs per gram (EPG) of small strongyles. Moreover, considering that there are no precise indications in donkeys, a value >300 EPG may be a safe recommendation. We have highlighted the main points of the discussion including the dynamics of helminth infections between the 2 species.
Jensen-Inaccuracy Information Measure Kharazmi, Omid; Shirazinia, Faezeh; Buono, Francesco ...
Entropy (Basel, Switzerland),
03/2023, Letnik:
25, Številka:
3
Journal Article
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The purpose of the paper is to introduce the Jensen-inaccuracy measure and examine its properties. Furthermore, some results on the connections between the inaccuracy and Jensen-inaccuracy measures ...and some other well-known information measures are provided. Moreover, in three different optimization problems, the arithmetic mixture distribution provides optimal information based on the inaccuracy information measure. Finally, two real examples from image processing are studied and some numerical results in terms of the inaccuracy and Jensen-inaccuracy information measures are obtained.
Results on Varextropy Measure of Random Variables Vaselabadi, Nastaran Marzban; Tahmasebi, Saeid; Kazemi, Mohammad Reza ...
Entropy (Basel, Switzerland),
03/2021, Letnik:
23, Številka:
3
Journal Article
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In 2015, Lad, Sanfilippo and Agrò proposed an alternative measure of uncertainty dual to the entropy known as extropy. This paper provides some results on a dispersion measure of extropy of random ...variables which is called varextropy and studies several properties of this concept. Especially, the varextropy measure of residual and past lifetimes, order statistics, record values and proportional hazard rate models are discussed. Moreover, the conditional varextropy is considered and some properties of this measure are studied. Finally, a new stochastic comparison method, named varextropy ordering, is introduced and some of its properties are presented.
Tsallis introduced a non-logarithmic generalization of Shannon entropy, namely Tsallis entropy, which is non-extensive. Sati and Gupta proposed cumulative residual information based on this ...non-extensive entropy measure, namely cumulative residual Tsallis entropy (CRTE), and its dynamic version, namely dynamic cumulative residual Tsallis entropy (DCRTE). In the present paper, we propose non-parametric kernel type estimators for CRTE and DCRTE where the considered observations exhibit an ρ-mixing dependence condition. Asymptotic properties of the estimators were established under suitable regularity conditions. A numerical evaluation of the proposed estimator is exhibited and a Monte Carlo simulation study was carried out.
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