scholarly journals Tree-weighting for multi-study ensemble learners

2019 ◽  
Author(s):  
Maya Ramchandran ◽  
Prasad Patil ◽  
Giovanni Parmigiani
Keyword(s):  
Random Forest ◽  
Random Forests ◽  
Training Process ◽  
Training Set ◽  
Prediction Ability ◽  
True Outcome ◽  
The Individual ◽  
Individual Trees ◽  
The Relationship ◽  
Shed Light

Multi-study learning uses multiple training studies, separately trains classifiers on individual studies, and then forms ensembles with weights rewarding members with better cross-study prediction ability. This article considers novel weighting approaches for constructing tree-based ensemble learners in this setting. Using Random Forests as a single-study learner, we perform a comparison of either weighting each forest to form the ensemble, or extracting the individual trees trained by each Random Forest and weighting them directly. We consider weighting approaches that reward cross-study replicability within the training set. We find that incorporating multiple layers of ensembling in the training process increases the robustness of the resulting predictor. Furthermore, we explore the mechanisms by which the ensembling weights correspond to the internal structure of trees to shed light on the important features in determining the relationship between the Random Forests algorithm and the true outcome model. Finally, we apply our approach to genomic datasets and show that our method improves upon the basic multi-study learning paradigm.

scholarly journals Prediction of Domestic Airline Tickets using Machine Learning

2021 ◽  
Vol 9 (VI) ◽  
pp. 666-674
Author(s):  
Pranita Rajure
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Random Forests ◽  
Learning Algorithm ◽  
Time Series Prediction ◽  
Complex Problem ◽  
Reasonable Prediction ◽  
The Individual ◽  
Domestic Airline ◽  
Individual Trees

Airlines usually keep their price strategies as commercial secrets and information is always asymmetric, it is difficult for ordinary customers to estimate future flight price changes. However, a reasonable prediction can help customers make decisions when to buy air tickets for a lower price. Flight price prediction can be regarded as a typical time series prediction problem. When you give customers a device that can help them save some money, they will pay you back with loyalty, which is priceless. Interesting fact: Fareboom users started spending twice as much time per session within a month of the release of an airfare price forecasting feature. Considering the features such as departure time, the number of days left for departure and time of the day it will give the best time to buy the ticket. Features are extracted from the collected data to apply Random Forest Machine Learning (ML) model. Then using this information, we are intended to build a system that can help buyers whether to buy a ticket or not. We have used Random Forest Algorithm which is a popular machine learning algorithm that belongs to the supervised learning technique. It can be used for both Classification and Regression problems in ML. It is based on the concept of ensemble learning, which is a process of combining multiple classifiers to solve a complex problem and to improve the performance of the model. With that said, random forests are a strong modelling technique and much more robust than a single decision tree. They aggregate many decision trees to limit over fitting as well as error due to bias and therefore yield useful results. Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation between them.

Islamic Revivalism in the Arab World and Its Dialogue with the West

2014 ◽  
Vol 31 (2) ◽  
pp. 22-42
Author(s):  
Mahmoud Dhaouadi
Keyword(s):  
Political Behavior ◽  
Arab World ◽  
Cultural Sociology ◽  
Arab Countries ◽  
The West ◽  
Religious Transformation ◽  
Arab Societies ◽  
The Individual ◽  
The Relationship ◽  
Shed Light

This paper seeks to underline two features of transformation in the Arab world since the late 1960s. First, that region’s religious transformation or ṣaḥwah(awakening) has been a general and overwhelming phenomenon. The pulse of Islam’s global surge can be easily observed at various levels of contemporary Arab countries: the individual and the collective, as well as their political behavior and organization. Second, the great tension between the West and Islam, particularly after 9/11, constituted a sort of change in the relationship between these two parties. I argue that these tensions could be reduced and minimized if the West were to improve its linguistic and cultural ties with Arab societies. The perspective of cultural sociology is very helpful in clarifying how to enhance such a dialogue. I shed light on these two topics through what I call a Homo Culturus perspective.

scholarly journals SEMANTIC BORROWING FOR GENERALIZED ZERO-SHOT LEARNING

2021 ◽  
Author(s):  
Xiao-wei CHEN
Keyword(s):  
Metric Learning ◽  
Training Process ◽  
Training Set ◽  
Shot Classification ◽  
Testing Data ◽  
Benchmark Datasets ◽  
Novel Method ◽  
Testing Semantics ◽  
The Relationship ◽  
Generalized Zero

<p>Generalized zero-shot learning (GZSL) is one of the most realistic problems, but also one of the most challenging problems due to the partiality of the classifier to supervised classes. Instance-borrowing methods and synthesizing methods solve this problem to some extent with the help of testing semantics, but therefore neither can be used under the class-inductive instance-inductive (CIII) training setting where testing data are not available, and the latter require the training process of a classifier after generating examples. In contrast, a novel method called Semantic Borrowing for improving GZSL methods with compatibility metric learning under CIII is proposed in this paper. It borrows similar semantics in the training set, so that the classifier can model the relationship between the semantics of zero-shot and supervised classes more accurately during training. In practice, the information of semantics of unseen or unknown classes would not be available for training while this approach does NOT need any information of semantics of unseen or unknown classes. The experimental results on representative GZSL benchmark datasets show that it can reduce the partiality of the classifier to supervised classes and improve the performance of generalized zero-shot classification.</p>

Manager or Craftsman

2021 ◽  
Author(s):  
Kai Jun Chen
Keyword(s):  
Qing Dynasty ◽  
Extended Family ◽  
Court System ◽  
Training Process ◽  
Building Projects ◽  
Empire Building ◽  
The Qing Dynasty ◽  
The Relationship ◽  
Representative Family ◽  
Shed Light

The chapter investigates how the ‘palace machine’ of the Qing dynasty reproduced (or systematically trained) particularly skilled bannermen as ethnically-marked official experts. By mapping out these bannermen’s education, training process, and official appointments, I explain how the court system perpetuated the administrative privilege of bannermen families and how specific skills of different generations matched the particular demands of empire building projects of the Qing dynasty in different stages. I focus on a representative family, the Wanggiyan/ Wanyan clan, generations of which served the court within the institutional framework of the Imperial Household Department. Placing this extended family in the context of peer bannermen equipped with specialized skills allows me to shed light on the larger issue of the relationship between hereditary status and specialized skills in the Qing palace machine.

Deuteronomy and Numbers

2012 ◽  
Vol 3 (2) ◽  
pp. 141-165
Author(s):  
Nathan MacDonald
Keyword(s):  
Complex Relationship ◽  
Narrative Space ◽  
Promised Land ◽  
The Individual ◽  
The Relationship ◽  
Continuous Narrative ◽  
Shed Light

The books of Numbers and Deuteronomy narrate a number of the same stories; Deut 1–3 even covers the same narrative space as the book of Numbers: the forty years or so from Sinai to the plains of Moab. This article will examine the complex relationship between these two books by considering the narratives about that time in the wilderness. These will be addressed in the following clusters: narratives told in Numbers and Deuteronomy; narratives told in Numbers and alluded to in Deuteronomy; and narratives in Numbers that are not told in Deuteronomy. These will be examined in order to shed light on the individual books of Numbers and Deuteronomy, the relationship between them, and the question of whether there was a pre-Deuteronomic narrative that retold how Israel went from the desert to the edge of the promised land. I will argue that there is no evidence for a continuous narrative tracing Israel’s journey from Sinai to Moab prior to the composition of Deut 1–3. The authors of the narratives in Numbers are indebted to this Deuteronomistic account. However, for the readers of the Pentateuch, Deut 1–3 appears as a concise summary of what has preceded, with the most important issues highlighted.

scholarly journals Aggregated Recommendation through Random Forests

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Heng-Ru Zhang ◽  
Fan Min ◽  
Xu He
Keyword(s):  
Random Forest ◽  
Recommender Systems ◽  
Random Forests ◽  
Decision Table ◽  
Data Conversion ◽  
Training Set ◽  
Training Stage ◽  
Testing Stage ◽  
Rating Information ◽  
New Item

Aggregated recommendation refers to the process of suggesting one kind of items to a group of users. Compared to user-oriented or item-oriented approaches, it is more general and, therefore, more appropriate for cold-start recommendation. In this paper, we propose a random forest approach to create aggregated recommender systems. The approach is used to predict the rating of a group of users to a kind of items. In the preprocessing stage, we merge user, item, and rating information to construct an aggregated decision table, where rating information serves as the decision attribute. We also model the data conversion process corresponding to the new user, new item, and both new problems. In the training stage, a forest is built for the aggregated training set, where each leaf is assigned a distribution of discrete rating. In the testing stage, we present four predicting approaches to compute evaluation values based on the distribution of each tree. Experiments results on the well-known MovieLens dataset show that the aggregated approach maintains an acceptable level of accuracy.

scholarly journals SEMANTIC BORROWING FOR GENERALIZED ZERO-SHOT LEARNING

2021 ◽  
Author(s):  
Xiao-wei CHEN
Keyword(s):  
Metric Learning ◽  
Training Process ◽  
Training Set ◽  
Shot Classification ◽  
Testing Data ◽  
Benchmark Datasets ◽  
Novel Method ◽  
Testing Semantics ◽  
The Relationship ◽  
Generalized Zero

<p>Generalized zero-shot learning (GZSL) is one of the most realistic problems, but also one of the most challenging problems due to the partiality of the classifier to supervised classes. Instance-borrowing methods and synthesizing methods solve this problem to some extent with the help of testing semantics, but therefore neither can be used under the class-inductive instance-inductive (CIII) training setting where testing data are not available, and the latter require the training process of a classifier after generating examples. In contrast, a novel method called Semantic Borrowing for improving GZSL methods with compatibility metric learning under CIII is proposed in this paper. It borrows similar semantics in the training set, so that the classifier can model the relationship between the semantics of zero-shot and supervised classes more accurately during training. In practice, the information of semantics of unseen or unknown classes would not be available for training while this approach does NOT need any information of semantics of unseen or unknown classes. The experimental results on representative GZSL benchmark datasets show that it can reduce the partiality of the classifier to supervised classes and improve the performance of generalized zero-shot classification.</p>

Islamic Revivalism in the Arab World and Its Dialogue with the West

2014 ◽  
Vol 31 (2) ◽  
pp. 22-42
Author(s):  
Mahmoud Dhaouadi
Keyword(s):  
Political Behavior ◽  
Arab World ◽  
Cultural Sociology ◽  
Arab Countries ◽  
The West ◽  
Religious Transformation ◽  
Arab Societies ◽  
The Individual ◽  
The Relationship ◽  
Shed Light

This paper seeks to underline two features of transformation in the Arab world since the late 1960s. First, that region’s religious transformation or ṣaḥwah(awakening) has been a general and overwhelming phenomenon. The pulse of Islam’s global surge can be easily observed at various levels of contemporary Arab countries: the individual and the collective, as well as their political behavior and organization. Second, the great tension between the West and Islam, particularly after 9/11, constituted a sort of change in the relationship between these two parties. I argue that these tensions could be reduced and minimized if the West were to improve its linguistic and cultural ties with Arab societies. The perspective of cultural sociology is very helpful in clarifying how to enhance such a dialogue. I shed light on these two topics through what I call a Homo Culturus perspective.

Accent Policy and Accent Modification Enterprises as Potential Indicators of Intercultural Power Relations: A Call for an Updated Research Agenda

2013 ◽  
Vol 3 (1) ◽  
pp. 22-33 ◽  
Author(s):  
Brynne D. Ovalle ◽  
Rahul Chakraborty
Keyword(s):  
International Relations ◽  
Identity Construction ◽  
Social Theory ◽  
Power Relations ◽  
Linguistic Diversity ◽  
Cultural Organization ◽  
Using Data ◽  
The Individual ◽  
The Impact ◽  
The Relationship

This article has two purposes: (a) to examine the relationship between intercultural power relations and the widespread practice of accent discrimination and (b) to underscore the ramifications of accent discrimination both for the individual and for global society as a whole. First, authors review social theory regarding language and group identity construction, and then go on to integrate more current studies linking accent bias to sociocultural variables. Authors discuss three examples of intercultural accent discrimination in order to illustrate how this link manifests itself in the broader context of international relations (i.e., how accent discrimination is generated in situations of unequal power) and, using a review of current research, assess the consequences of accent discrimination for the individual. Finally, the article highlights the impact that linguistic discrimination is having on linguistic diversity globally, partially using data from the United Nations Educational, Scientific and Cultural Organization (UNESCO) and partially by offering a potential context for interpreting the emergence of practices that seek to reduce or modify speaker accents.

Investigating the Relationship Between Self-Esteem and Stigma Among Young Adults With History of Suicide Attempts

Crisis ◽  
2016 ◽  
Vol 37 (4) ◽  
pp. 265-270 ◽  
Author(s):  
Meshan Lehmann ◽  
Matthew R. Hilimire ◽  
Lawrence H. Yang ◽  
Bruce G. Link ◽  
Jordan E. DeVylder
Keyword(s):  
Young Adults ◽  
Suicide Attempts ◽  
Self Esteem ◽  
High Risk Population ◽  
High Functioning ◽  
People With Mental Illness ◽  
History Of ◽  
The Individual ◽  
The Impact ◽  
The Relationship

Abstract. Background: Self-esteem is a major contributor to risk for repeated suicide attempts. Prior research has shown that awareness of stigma is associated with reduced self-esteem among people with mental illness. No prior studies have examined the association between self-esteem and stereotype awareness among individuals with past suicide attempts. Aims: To understand the relationship between stereotype awareness and self-esteem among young adults who have and have not attempted suicide. Method: Computerized surveys were administered to college students (N = 637). Linear regression analyses were used to test associations between self-esteem and stereotype awareness, attempt history, and their interaction. Results: There was a significant stereotype awareness by attempt interaction (β = –.74, p = .006) in the regression analysis. The interaction was explained by a stronger negative association between stereotype awareness and self-esteem among individuals with past suicide attempts (β = –.50, p = .013) compared with those without attempts (β = –.09, p = .037). Conclusion: Stigma is associated with lower self-esteem within this high-functioning sample of young adults with histories of suicide attempts. Alleviating the impact of stigma at the individual (clinical) or community (public health) levels may improve self-esteem among this high-risk population, which could potentially influence subsequent suicide risk.

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