نتایج جستجو برای: طبقهبند k نزدیکترین همسایه knn
تعداد نتایج: 381296 فیلتر نتایج به سال:
K-Nearest Neighbor (KNN) is one of the most popular algorithms for data classification. Many researchers have found that the KNN algorithm accomplishes very good performance in their experiments on different datasets. The traditional KNN text classification algorithm has limitations: calculation complexity, the performance is solely dependent on the training set, and so on. To overcome these li...
Hybrid model is a popular forecasting model in renewable energy related forecasting applications. Wind speed forecasting, as a common application, requires fast and accurate forecasting models. This paper introduces an Empirical Mode Decomposition (EMD) followed by a k Nearest Neighbor (kNN) hybrid model for wind speed forecasting. Two configurations of EMD-kNN are discussed in details: an EMD-...
چکیده مقدمه: تشخیص زودهنگام سرطان پستان نقش بسیار کلیدی در درمان و حیات بیمار ایفا میکند. امروزه با استفاده از خصوصیات استخراج شده از آزمایش آسپیراسیون سوزنی و الگوریتمهای دادهکاوی میتوان روشهای نوین و هوشمندی در نظام سلامت و درمان ارایه داد که با دقت بالایی قادر به تشخیص سرطان پستان باشند، هدف از انجام این مطالعه تشخیص سرطان پستان با استفاده از کاهش دو مرحلهای ویژگیهای استخراج شده آسپ...
Medical Data mining is the process of extracting hidden patterns from medical data. This paper presents the development of a hybrid model for classifying Pima Indian diabetic database (PIDD). The model consists of three stages. In the first stage, K-means clustering is used to identify and eliminate incorrectly classified instances. In the second stage Genetic algorithm (GA) and Correlation bas...
K-Nearest Neighbor (KNN) is one of the most popular algorithms for data classification. Many researchers have found that the KNN algorithm accomplishes very good performance in their experiments on different datasets. The traditional KNN text classification algorithm has limitations: calculation complexity, the performance is solely dependent on the training set, and so on. To overcome these li...
High-dimensional problems arising from robot motion planning, biology, data mining, and geographic information systems often require the computation of k nearest neighbor (knn) graphs. The knn graph of a data set is obtained by connecting each point to its k closest points. As the research in the above-mentioned fields progressively addresses problems of unprecedented complexity, the demand for...
Classification of spatial data has become important due to the fact that there are huge volumes of spatial data now available holding a wealth of valuable information. In this paper we consider the classification of spatial data streams, where the training dataset changes often. New training data arrive continuously and are added to the training set. For these types of data streams, building a ...
Associative classification usually generates a large set of rules. Therefore, it is inevitable that an instance matches several rules which classes are conflicted. In this paper, a new framework called Associative Classification with KNN (AC-KNN) is proposed, which uses an improved KNN algorithm to address rule conflicts. Traditional K-Nearest Neighbor (KNN) is low efficient due to its calculat...
In this paper, a novel prototype reduction algorithm is proposed, which aims at reducing the storage requirement and enhancing the online speed while retaining the same level of accuracy for a K-nearest neighbor (KNN) classifier. To achieve this goal, our proposed algorithm learns the weighted similarity function for a KNN classifier by maximizing the leave-one-out cross-validation accuracy. Un...
بیان احساس در ارتباطات روزمره از جایگاه ویژه ای برخوردار است. از جمله بسترهای نمود احساس، گفتار است. از این رو، یکی از جنبه های مهم در طبیعی سازی ارتباط میان انسان و ماشین، تشخیص حس گفتار و تولید بازخورد متناسب با احساس درک شده است. باوجود پیشرفت های گسترده در حوزه پردازش گفتار، استخراج و درک احساس پنهان در گفتار انسان، همچون خشم، شادی و جز این ها، از یک سو و تولید گفتار احساسی مناسب از سوی دیگ...
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