نتایج جستجو برای: parametric knn method in pilambara
تعداد نتایج: 17244768 فیلتر نتایج به سال:
abstract biometric access control is an automatic system that intelligently provides the access of special actions to predefined individuals. it may use one or more unique features of humans, like fingerprint, iris, gesture, 2d and 3d face images. 2d face image is one of the important features with useful and reliable information for recognition of individuals and systems based on this ...
the methods which are used to analyze microstrip antennas, are divited into three categories: empirical methods, semi-empirical methods and full-wave analysis. empirical and semi-empirical methods are generally based on some fundamental simplifying assumptions about quality of surface current distribution and substrate thickness. thses simplificatioms cause low accuracy in field evaluation. ful...
a significant problem in multicarrier communication systems is the necessity to reduce the value of papr (peak-to-average power ratio) of transmitting signal. in this thesis we study the effect of the system parameters such as coding and modulation types on papr and ultimate ber in a mc-cdma system. in this study we consider fading channel as well as the nonlinearity of transmitter’s amplifier ...
abstract present research considered to examine and compare shahrray 14 years girls and boys narrative concerning with their responsibilities in this research, statistical society are 14 years girls and boys of shahrry . for performing this research. first, 14 years of 50 boys and 50 girls were selected in accidental method and have filled memati hormaled adolescents responsibility questioner...
k-nearest neighbour algorithm is a non-parametric machine learning algorithm generally used for classification. It is also known as instance based learning or lazy learning. K-NN algorithm can also be adapted for regression that is for estimating continuous variables. In this research paper the researcher endow with a generalized K-nearest algorithm used for predicting a continuous value. In or...
K nearest neighbor algorithm is one of the most frequently used techniques in data mining for its integrity and performance. Though the KNN algorithm is highly effective in many cases, it has some essential deficiencies, which affects the classification accuracy of the algorithm. First, the effectiveness of the algorithm is affected by redundant and irrelevant features. Furthermore, this algori...
abstract: in this thesis, we focus to class of convex optimization problem whose objective function is given as a linear function and a convex function of a linear transformation of the decision variables and whose feasible region is a polytope. we show that there exists an optimal solution to this class of problems on a face of the constraint polytope of feasible region. based on this, we dev...
the rationale behind the present study is that particular learning strategies produce more effective results when applied together. the present study tried to investigate the efficiency of the semantic-context strategy alone with a technique called, keyword method. to clarify the point, the current study seeked to find answer to the following question: are the keyword and semantic-context metho...
Collaborative filtering has been very successful in both research and E-commence applications. One of the most popular collaborative filtering algorithms is the k-Nearest Neighbor (KNN) method, which finds k nearest neighbors for a given user to predict his interests. Previous research on KNN algorithm usually suffers from the data sparseness problem, because the quantity of items users voted i...
objective: diabetes is one of the most common metabolic diseases. earlier diagnosis of diabetes and treatment of hyperglycemia and related metabolic abnormalities is of vital importance. diagnosis of diabetes via proper interpretation of the diabetes data is an important classification problem. classification systems help the clinicians to predict the risk factors that cause the diabetes or pre...
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