An Empirical Comparison of Semantics for Quantified Vague Sentences by Alexandre Cremers, Julija Kalvelyte

“…We present an experiment that gathers data on naïve speakers’ interpretation of such sentences after collecting their judgment on the applicability of the vague predicate for each individual in the restrictor. …”
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Adversarial Attack Detection in Smart Grids Using Deep Learning Architectures by Stephanie Ness

“…After analyses of the performances of Logistic Regression, Perceptron, Gaussian Naive Bayes and Multi-Layer Perceptron, LSTM network has better results with an accuracy of 99.81%. …”
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Teaching the Future Teachers: A Teacher Educator’s Self-Study in Making Science Relevant, Useful and Meaningful for New Zealand Pre-Service Teachers by Steven Sexton

“…The initial NSAAQ results indicated where the pre-service teachers understanding of the nature of science were naïve and what aspects needed to be addressed over the course of the programme. …”
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Ироническое начало в фельетоне Киев-город Михаила Булгакова by Antoni Bortnowski

“…The analysis of the techniques used by the writer in the text of Kiev, the City (e.g. the naive narrator’s mask, a combination of pompous style and colloquial speech) is carried out in order to prove that the feuilleton, in its style and ideas expressed, also shows the author’s rejection of post-revolutionary reality and his attempt to overcome the trauma of the past through laughter. …”
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A Critique of the Book Understanding Social Science from the Perspective of Actor-Network Theory by Rahman Sharifzadeh

“…In the context of critical realism, Trigg criticizes in a good and detailed way many of the common dichotomies, amongst which naive realism / non-realism is most important. Although Trigg attempts to go away from positivistic and non-critical methodologies, and in result opens up a way for rational evaluation and judgment, as we shall see, he does not develop his methodology very well; moreover, his understanding of what society is and what social structures and realities are made of may endanger the empirical aspect of his methodology. …”
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The modeling of earnings per share of Polish companies for the post-financial crisis period using random walk and ARIMA models by Wojciech Kuryłek

“…Contrary to the findings regarding the US market, this time-series behavior is well described by the naive seasonal random walk model, whereas in the US the most adequate models are of a more sophisticated ARIMA type. …”
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A Multiperiod Equilibrium Pricing Model by Minsuk Kwak, Traian A. Pirvu, Huayue Zhang

“…Both subgame perfect strategy and naive strategy are considered and the corresponding equilibrium prices are derived. …”
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Application on text classification of telecom user complaints based on GRW and FastText model by Jin ZHAO, Xiaojun YANG

“…With the widespread application of neural network, the application of neural network to natural language processing text classification problems has become an effective solution.The customer service center of telecom operator collected user complaint information from multiple channels.In order to automatically classify the complaint text information and assign it to the specific responsible department for processing and reply, enhancing customer perception further, a textclassification method based on GRW and FastTextmodel was proposed.Firstly, the GRW model was used to select the features of the complaint text, extract effective feature words, and then a user complaint text classification method based on FastText model was constructed.Experiments on public datasets and a complaint text data by one of telecom company show that the text classification method based on GRW and FastText model is better than naive Bayes, bidirectional LSTM and Bert pre-trained model in accuracy, Kappa coefficient and Hamming loss.…”
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FOUR CRITERIA FOR IDENTIFYING THE SOCIALLY MARGINAL IN THE SOCIAL CONTEXT OF EARLY CHRISTIANITY REFLECTED IN THE NEW TESTAMENT by I.C. Berg

“…Social minority is not a statistical concept. The most naïve and flawed understanding of social minority has to do with the “quantity” of people. …”
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Design and implementation of spam filtering system based on topic model by Xiaohuai KOU, Hua CHENG

“…Spam filtering technology plays a key role in many areas including information security,transmission efficiency,and automatic information classification.However,the emergence of spam affects the user's sense of experience,and can cause unnecessary economic and time loss.The deficiency of spam filtering technology was researched,and a method of spam classification based on naive Bayesian was put forward based on multiple keywords.In the subject of mail,the theme model was used by LDA to get the related subject and keyword of the message,and Word2Vec was further used to search keyword synonyms and related words,extending the keyword collection.In the classification of mails,the transcendental probability of the words in the training dataset was obtained by statistical learning.Based on the extended keyword collection and its probability,the joint probability of a subject and a message was deduced by the Bayesian formula as a basis for the spam judgment.At the same time,the spam filtering system based on topic model was simple and easy to apply.By comparing experiments with other typical spam filtering method,it is proved that the method of spam classification based on theme model and the improved method based on Word2Vec can effectively improve the accuracy of spam filtering.…”
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Area under the ROC Curve has the most consistent evaluation for binary classification. by Jing Li

“…Analyzing 156 data scenarios, 18 model evaluation metrics and five commonly used machine learning models as well as a naive random guess model, I find that evaluation metrics that are less influenced by prevalence offer more consistent evaluation of individual models and more consistent ranking of a set of models. …”
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The Impact of Investor Sentiment on Direction of Stock Price Changes: Evidence from the Polish Stock Market by Kamil Polak

“…In order to examine the predictive power of sentiment, six machine learning models were used: Decision Tree Classifier, Random Forest Classifier, XGBoost Classifier, KNN Classifier, SVC and Gaussian Naive Bayes Classifier. Empirical results show that the sentiment of news headlines has no significant explanatory power for the direction of stock price changes in one-day time frame.…”
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Clinical XLNet-based End-to-End Knowledge Discovery on Clinical Text Data using Natural Language Processing by Naveen S. Pagad, Pradeep Nijalingappa, Tulika Chakrabarti, Prasun Chakrabarti, Pugazhenthan Thangaraju

“…To predict the dependent clinical relation association, the multinomial Naïve Bayes probability function has been incorporated. …”
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Gulliver and the Gentle Reader by Claude RAWSON

“…From the beginning, the reader is wrongfooted by an unusually quarrelsome intimacy on the part of the narrative, and a constantly shifting instability in the register of the irony. The naïve Gulliver’s praise of humanity, as well as his deranged condemnation of it in the final book, are both separate from the implied voice of the satirist, which always makes itself felt. …”
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Mechanisms behind Functional Avidity Maturation in T Cells by Marina Rode von Essen, Martin Kongsbak, Carsten Geisler

“…Nevertheless, antigen-primed T cells significantly increase their antigen responsiveness compared to antigen-inexperienced (naïve) T cells in a process called functional avidity maturation. …”
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Ipilimumab: A First-in-Class  T-Cell Potentiator for Metastatic Melanoma by Bartosz Chmielowski

“…Ipilimumab, a fully human anti-cytotoxic T-lymphocyte antigen-4 monoclonal antibody that potentiates antitumor T-cell responses, has demonstrated improved survival in previously treated and treatment-naïve patients with unresectable stage III/IV melanoma. …”
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User behavior pattern mining method based on multi-dimension and multi-granularity analysis in telecom networks by Xiaotao CHENG, Lixin JI, Ruiyang HUANG, Hongtao YU, Yizhuo YANG

“…In order to better understand the behavior of users in telecom networks,it takes CDR (call detail record) data of large-scale telecom network as the research object.By using the mixed probability model and feature engineering method,the multi-dimension characteristics of the call time,call frequency and connections are analyzed from the perspective of user groups and individuals.It is further refined from different time granularities such as hour,day,and week to realize effective discovery of call behavior patterns for different user groups.The distribution characteristics of user behavior are modeled by mixed probability model,which solves the problem of describing the distribution characteristics such as user's call time and frequency.Based on the dataset of a regional telecom network,the performance of decision tree,naive Bayes and SVM classification algorithm are compared.It proves the validity and computational feasibility of the proposed method.The differences in communication behavior patterns of different groups are also compared by taking the service numbers like express,flight and bank as examples.…”
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Average Analytic Ranks of Elliptic Curves over Number Fields by Tristan Phillips

“…In particular, under the assumptions that all elliptic curves over a number field K are modular and have L-functions which satisfy the Generalized Riemann Hypothesis, we show that the average analytic rank of isomorphism classes of elliptic curves over K is bounded above by $(9\deg (K)+1)/2$ , when ordered by naive height. A key ingredient in the proof is giving asymptotics for the number of elliptic curves over an arbitrary number field with a prescribed local condition; these results are obtained by proving general results for counting points of bounded height on weighted projective stacks with a prescribed local condition, which may be of independent interest.…”
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Quality Control of Olive Oils Using Machine Learning and Electronic Nose by Emre Ordukaya, Bekir Karlik

“…Different machine learning classifiers such as Naïve Bayesian, K-Nearest Neighbors (k-NN), Linear Discriminate Analysis (LDA), Decision Tree, Artificial Neural Networks (ANN), and Support Vector Machine (SVM) were used. …”
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Analisis Sentimen untuk Evaluasi Reputasi Merek Motor XYZ Berkaitan dengan Isu Rangka Motor di Twitter Menggunakan Pendekatan Machine Learning by Ferdian Maulana Akbar, Robby Hermansyah, Sofian Lusa, Dana Indra Sensuse, Nadya Safitri, Damayanti Elisabeth

“…We used sentiment analysis with word clouds, trend and distribution analysis, and compared five machine learning algorithms: Naïve Bayes, Decision Tree, Support Vector Machine, Logistic Regression, and Random Forest. …”
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