scholarly journals FBSEM: A Novel Feature-Based Stacked Ensemble Method for Sentiment Analysis

2020 ◽  
Vol 12 (6) ◽  
pp. 11-22
Author(s):  
Yasin Görmez ◽  
◽  
Yunus E. Işık ◽  
Mustafa Temiz ◽  
Zafer Aydın
Keyword(s):  
Sentiment Analysis ◽  
Cross Validation ◽  
Emotional State ◽  
Ensemble Methods ◽  
Extraction Methods ◽  
Error Rates ◽  
Ensemble Method ◽  
Learning Tasks ◽  
Feature Based ◽  
The Individual

Sentiment analysis is the process of determining the attitude or the emotional state of a text automatically. Many algorithms are proposed for this task including ensemble methods, which have the potential to decrease error rates of the individual base learners considerably. In many machine learning tasks and especially in sentiment analysis, extracting informative features is as important as developing sophisticated classifiers. In this study, a stacked ensemble method is proposed for sentiment analysis, which systematically combines six feature extraction methods and three classifiers. The proposed method obtains cross-validation accuracies of 89.6%, 90.7% and 67.2% on large movie, Turkish movie and SemEval-2017 datasets, respectively, outperforming the other classifiers. The accuracy improvements are shown to be statistically significant at the 99% confidence level by performing a Z-test.

scholarly journals Feature-Based Opinion Mining and Managed Machine Learning with Sentiment Classification Models

2019 ◽  
Vol 9 (2) ◽  
pp. 3992-3998
Keyword(s):  
Machine Learning ◽  
Sentiment Analysis ◽  
Language Processing ◽  
Opinion Mining ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
K Nearest Neighbors ◽  
Data Intensive ◽  
Learning Tasks ◽  
Feature Based

Sentiment Analysis is individuals' opinions and feedbacks study towards a substance, which can be items, services, movies, people or events. The opinions are mostly expressed as remarks or reviews. With the social network, gatherings and websites, these reviews rose as a significant factor for the client’s decision to buy anything or not. These days, a vast scalable computing environment provides us with very sophisticated way of carrying out various data-intensive natural language processing (NLP) and machine-learning tasks to examine these reviews. One such example is text classification, a compelling method for predicting the clients' sentiment. In this paper, we attempt to center our work of sentiment analysis on movie review database. We look at the sentiment expression to order the extremity of the movie reviews on a size of 0(highly disliked) to 4(highly preferred) and perform feature extraction and ranking and utilize these features to prepare our multilabel classifier to group the movie review into its right rating. This paper incorporates sentiment analysis utilizing feature-based opinion mining and managed machine learning. The principle center is to decide the extremity of reviews utilizing nouns, verbs, and adjectives as opinion words. In addition, a comparative study on different classification approaches has been performed to determine the most appropriate classifier to suit our concern problem space. In our study, we utilized six distinctive machine learning algorithms – Naïve Bayes, Logistic Regression, SVM (Support Vector Machine), RF (Random Forest) KNN (K nearest neighbors) and SoftMax Regression.

scholarly journals Recognition of Emotional State Based On Handwriting Analysis and Psychological Assessment

2019 ◽  
Vol 8 (6) ◽  
pp. 4395-4402
Keyword(s):  
Psychological Assessment ◽  
Signal Analysis ◽  
Cross Validation ◽  
Emotional State ◽  
Psychological Treatment ◽  
Negative Emotions ◽  
Sample Analysis ◽  
Handwriting Analysis ◽  
Test Dataset ◽  
The Individual

Emotions describe the physiological states of an individual and are generated subconsciously. They motivate, organize, and guide perception, thought, and action. Emotions can be positive or negative. Negative emotions manifest in the form of depression, anxiety and stress. It is necessary to identify negative emotions of an individual who might be in the need for counseling or psychological treatment. Body signal analysis, handwriting analysis, and psychological assessment are some mechanisms to measure them. In this paper, emotional state is being measured through the person’s handwriting sample analysis and psychological assessment. Psychological assessment is done by using the results of DASS questionnaire attempted by the individual. Convolutional Neural Network (CNN) algorithm is used to find the emotional state of an individual from his/her handwriting sample. Comparative analysis is performed to suggest counseling/medication if required. The final CNN model is formed by using the ensemble method over cross-validation models. The accuracy achieved by the CNN model over the test dataset is 91.25%.

scholarly journals Biological Effect of Different Spinach Extracts in Comparison with the Individual Components of the Phytocomplex

Foods ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 382
Author(s):  
Laura Arru ◽  
Francesca Mussi ◽  
Luca Forti ◽  
Annamaria Buschini
Keyword(s):  
Antioxidant Defense ◽  
Extraction Methods ◽  
Oxidizing Agent ◽  
Endogenous Reactive Oxygen Species ◽  
Dependent Activity ◽  
Main Components ◽  
The Individual ◽  
Dose Dependent ◽  
Higher Doses ◽  
Oxidative Insult

The Mediterranean-style diet is rich in fruit and vegetables and has a great impact on the prevention of major chronic diseases, such as cardiovascular diseases and cancer. In this work we investigated the ability of spinach extracts obtained by different extraction methods and of the single main components of the phytocomplex, alone or mixed, to modulate proliferation, antioxidant defense, and genotoxicity of HT29 human colorectal cells. Spinach extracts show dose-dependent activity, increasing the level of intracellular endogenous reactive oxygen species (ROS) when tested at higher doses. In the presence of oxidative stress, the activity is related to the oxidizing agent involved (H2O2 or menadione) and by the extraction method. The single components of the phytocomplex, alone or mixed, do not alter the intracellular endogenous level of ROS but again, in the presence of an oxidative insult, the modulation of antioxidant defense depends on the oxidizing agent used. The application of the phytocomplex extracts seem to be more effective than the application of the single phytocomplex components.

scholarly journals Ensemble bootstrap methodology for forecasting dynamic growth processes using differential equations: application to epidemic outbreaks

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Gerardo Chowell ◽  
Ruiyan Luo
Keyword(s):  
Differential Equations ◽  
Ensemble Method ◽  
Transmission Model ◽  
Logistic Growth ◽  
Ensemble Modeling ◽  
Growth Processes ◽  
Probabilistic Forecasts ◽  
Forecasting Performance ◽  
Dynamic Growth ◽  
The Individual

AbstractBackgroundEnsemble modeling aims to boost the forecasting performance by systematically integrating the predictive accuracy across individual models. Here we introduce a simple-yet-powerful ensemble methodology for forecasting the trajectory of dynamic growth processes that are defined by a system of non-linear differential equations with applications to infectious disease spread.MethodsWe propose and assess the performance of two ensemble modeling schemes with different parametric bootstrapping procedures for trajectory forecasting and uncertainty quantification. Specifically, we conduct sequential probabilistic forecasts to evaluate their forecasting performance using simple dynamical growth models with good track records including the Richards model, the generalized-logistic growth model, and the Gompertz model. We first test and verify the functionality of the method using simulated data from phenomenological models and a mechanistic transmission model. Next, the performance of the method is demonstrated using a diversity of epidemic datasets including scenario outbreak data of theEbola Forecasting Challengeand real-world epidemic data outbreaks of including influenza, plague, Zika, and COVID-19.ResultsWe found that the ensemble method that randomly selects a model from the set of individual models for each time point of the trajectory of the epidemic frequently outcompeted the individual models as well as an alternative ensemble method based on the weighted combination of the individual models and yields broader and more realistic uncertainty bounds for the trajectory envelope, achieving not only better coverage rate of the 95% prediction interval but also improved mean interval scores across a diversity of epidemic datasets.ConclusionOur new methodology for ensemble forecasting outcompete component models and an alternative ensemble model that differ in how the variance is evaluated for the generation of the prediction intervals of the forecasts.

Estimating Heterogeneous Treatment Effects and the Effects of Heterogeneous Treatments with Ensemble Methods

2017 ◽  
Vol 25 (4) ◽  
pp. 413-434 ◽  
Author(s):  
Justin Grimmer ◽  
Solomon Messing ◽  
Sean J. Westwood
Keyword(s):  
Treatment Effects ◽  
Ensemble Methods ◽  
Ensemble Method ◽  
Superior Performance ◽  
Accurate Estimation ◽  
Randomized Experiments ◽  
Heterogeneous Treatment Effects ◽  
Data Set ◽  
Heterogeneous Effects ◽  
The Ensemble Method

Randomized experiments are increasingly used to study political phenomena because they can credibly estimate the average effect of a treatment on a population of interest. But political scientists are often interested in how effects vary across subpopulations—heterogeneous treatment effects—and how differences in the content of the treatment affects responses—the response to heterogeneous treatments. Several new methods have been introduced to estimate heterogeneous effects, but it is difficult to know if a method will perform well for a particular data set. Rather than using only one method, we show how an ensemble of methods—weighted averages of estimates from individual models increasingly used in machine learning—accurately measure heterogeneous effects. Building on a large literature on ensemble methods, we show how the weighting of methods can contribute to accurate estimation of heterogeneous treatment effects and demonstrate how pooling models lead to superior performance to individual methods across diverse problems. We apply the ensemble method to two experiments, illuminating how the ensemble method for heterogeneous treatment effects facilitates exploratory analysis of treatment effects.

PRAGMATIC POTENTIAL OF AUTHOR’S AND TRANSFORMED PHRASEOLOGIES IN THE WORK OF CARLOS RUIZ ZAFÓN «THE PRISONER OF HEAVEN»

2021 ◽  
pp. 18-28
Author(s):  
A. Yu. Bovsunivska A. Yu.
Keyword(s):  
Emotional State ◽  
Spanish Language ◽  
The Novel ◽  
Unique Combination ◽  
Textual Space ◽  
Different Types ◽  
General Linguistic ◽  
The Individual ◽  
Pragmatic Aspects ◽  
Individual Style

The article is devoted to the study of pragmatic aspects of the use of phraseology in the textual space of Carlos Ruiz Safón’s novel «Prisoner of Heaven». One of the defining features of the individual style of this well-known modern Spanish writer is the metaphoricity and figuration of aristic expression, the saturation of the text with phraseological units that play a significant role in creating a pragmatic charge of the work of art. Along with general linguistic phraseological units, which include commonly-used vocabulary, the author uses dialectal and authorial phraseological units, which is a feature of his individual style. All three designated groups of phraseological units mostly reflect the negative psychophysical and emotional state of the characters. The author uses dialectal, individually-authorial and modified phraseological units, which is a feature of his individual style. It is determined that transformation is one of the most productive and most effective ways to update linguistic means in works of art. Author’s modification of FU leads to a change in the semantics and structure of expression, gives it a more expressive or emotional coloring. Transformed phraseology is limited to individual usage and is subject to the context of the work. Modified FUs in the Zafón’s artistic space acquire certain aesthetic and artistic qualities. Their modification is mainly to create the desired stylistic effect – to achieve emotional or expressive expression, which increases the reader’s interest, focuses on the content, issues of the work, as well as reveals the potential expressive potential of the Spanish language. In the transformed FUs, not just a new meaning is traced, but a combination of the well-known and the occasional. The unique combination of different types of phraseological units in the novel is considered a manifestation of individual style and makes a representation of the individually-authorial linguistic picture of the world more expressive.

Atlantic, Pacific, and world-wide features in English-lexicon contact languages

2001 ◽  
Vol 22 (2) ◽  
pp. 157-208 ◽  
Author(s):  
Philip Baker ◽  
Magnus Huber
Keyword(s):  
World Wide ◽  
Statistical Feature ◽  
The Pacific ◽  
Geographical Regions ◽  
Feature Based ◽  
The Individual ◽  
Shed Light

This article analyzes the earliest known attestations of 302 lexical, functional, and grammatical features in 13 English-lexicon contact languages in the Atlantic and the Pacific. The main aims are (i) to shed light on the historical relationships between the individual varieties, (ii) to learn about the mechanisms at work in their genesis and development, and (iii) to examine the significance of features common to both geographical regions. Overall, our intention is to demonstrate that a statistical feature-based approach as proposed here can yield valuable insights into the development and interrelationships between Pidgins and Creoles.

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