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В статье кратко формулируется актуальность практико ориентированного подхода в современном китайском музыкальном образовании в сфере медно духового искусства. Данный подход обусловлен растущим числом в стране оркестровых коллективов и соответственно, возможностью трудоустройства выпускников профильных вузов. Указывается на отсутствие упорядоченной системы обучения молодых духовиков, качественного методического обеспечения уч ебного процесса, а также значительный разброс в профессиональном уровне, как преподавателей, так и их воспитанников в зависимости от конкретного учебного заведения, города и региона КНР. Практико-ориентированный подход в обучении специалистов-духовиков подразумевает изучение мотивационной готовности и предпочтений будущих выпускников относительно предполагаемого места работы, формирование востребованных профессиональных и личностных коммуникативных качеств, обращение к соответствующему репертуару в корреляции с определёнными технологическими задачами и т.д. Одним из ключевых компонентов такого подхода в современной вузовской подготовке специалистов в области медно духового искусства является формирование навыков оркестровой и ансамблевой игры молодых исполни телей. Создание разнообразных курсов по искусству игры в ансамбле – это лучшая возможность развивать музыкальные способности обучающихся. В основе такой подготовки лежит не только знание своего инструмента и мастерское владение им, но и внимание к звучанию других партий. Это позволяет быстро оценивать положение и соответствующим образом встраивать собственное исполнение в целостное звучание, не выделяясь, но и не теряясь в общей акустике. Проведение реформ в области музыкально-педагогического образования в КНР предусматривает совершенствование профессиональной подготовки студентов различных музыкальных специальностей в вузах, введения новых учебных стандартов, методического обеспечения и установок содержания процесса обучения. Практико ориентированный подход в этом контексте призван интегрировать существующие образовательные модели с инновационными разработками обучения студентов духовиков и соответственно скорректировать алгоритм учебного процесса., The article briefly formulates the relevance of the practice oriented approach in modern Chinese music education in the field of b rass art. This approach is due to the growing number of orchestra groups in the country and, accordingly, the possibility of employment of graduates of specialized universities. The author points out the lack of an orderly system of training young spiritua l teachers, high quality methodological support of the educational process, as well as a significant variation in the professional level of both teachers and their students, depending on the specific educational institution, c ity and region of the PRC. The practice oriented approach in the training of spiritual specialists involves the study of the motivational readiness and preferences of future graduates regarding the intended place of work, the formation of popular professional and personal communicative qualities, the appeal to the appropriate repertoire in correlation with certain technological tasks, etc. One of the key components of this approach in the modern university training of specialists in the field of brass art is the formation of the skills of orchestral and ensemble playing of young performers. Creating a variety of courses on the art of playing in an ensemble is the best opportunity to develop students ' musical abilities. At the heart of this training is not only knowledge of your instrume nt and masterful command of it, but also attention to the sound of other parts. This allows you to quickly assess the position and appropriately integrate your own performance into the overall sound, without standing out, but also without getting lost in t he overall acoustics. The implementation of reforms in the field of music and pedagogical education in the People's Republic of China provides for the improvement of professional training of students of various musical specialties in universities, the intr oduction of new educational standards, methodological support and guidelines for the content of the learning process. The practice oriented approach in this context is designed to integrate existing educational models with innovative developments in teachi ng spiritual students and adjust the algorithm of the educational process accordingly., Международный научно-исследовательский журнал, Выпуск 7 (109) 2021, Pages 152-155

Optimal selection of training samples is very difficult when multiple learning machines are used in classification. We investigated an approach to mining of training samples for multiple learning machines in computer-aided detection of lesions. Our approach starts from "weakness" analysis of a seed machine-learning (ML) model trained for a given task. The weakness is analyzed in the receiver-operating-characteristic (ROC) space in classification. The most to least "difficult" samples for the seed model are "mined" by dividing samples into N groups by the ROC scores. N ML models are trained with the mined N groups of training samples in an ensemble manner. We tested our approach in classification between 25 lesions and 489 non-lesions. Our ML ensemble trained with the mined samples achieved a performance higher than did an ML ensemble with manually selected training samples.

It is widely known that the best classifier for a given problem is often problem dependent and there is no one classification algorithm that is the best for all classification tasks. A natural question that arise is: can we combine multiple classification algorithms to achieve higher classification accuracy than a single one? That is the idea behind a class of methods called ensemble method. Ensemble method is defined as the combination of several classifiers with the aim of achieving lower classification error rate than using a single classifier. Ensemble methods have been applying to various applications ranging from computer aided medical diagnosis, computer vision, software engineering, to information retrieval. In this study, we focus on heterogeneous ensemble methods in which a fixed set of diverse learning algorithms are learned on the same training set to generate the different classifiers and the class prediction is then made based on the output of these classifiers (called Level1 data or meta-data). The research on heterogeneous ensemble methods is mainly focused on two aspects: (i) to propose efficient classifiers combining methods on meta-data to achieve high accuracy, and (ii) to optimize the ensemble by performing feature and classifier selection. Although various approaches related to heterogeneous ensemble methods have been proposed, some research gaps still exist First, in ensemble learning, the meta-data of an observation reflects the agreement and disagreement between the different base classifiers.