K - Nearest Neighbor
MKNN: Modified K-Nearest Neighbor
... In this paper, a new algorithm for improving the performance of KNN classifier is proposed which is called Modified K-Nearest Neighbor, MKNN. The proposed method which considerably improves the ...
4
Aplicação do algoritmo k-nearest neighbor para classificação de métodos de controle enzimático em frutas / K-nearest neighbor algorithm application for classification of enzymatic control methods in fruits
... algorithm, k-Nearest Neighbor (KNN), was used to classify and select the best studied ...algorithm, K-Nearest Neighbor (KNN), showed that the most satisfactory treatment was the ...
12
Estimating Stand Height and Tree Density in Pinus taeda plantations using in-situ data, airborne LiDAR and k-Nearest Neighbor Imputation
... the k-nearest neighbor (k-NN) ...non-parametric k-NN imputation method uses a set of predictor feature variables (X) to match each target pixel to a number (k) of most similar ...
15
An Improved k-Nearest Neighbor Classification Using Genetic Algorithm
... k-Nearest Neighbor (KNN) is one of the most popular algorithms for pattern ...taking k-neighbors, the GA is employed to take k-neighbors straightaway and then calculate the distance to ...
4
A Regression-based K nearest neighbor algorithm for gene function prediction from heterogeneous data
... Computational Biology held at Whistler, Canada on December 18th, 2004.. This.[r] ...
3
Survey of Classification Techniques in Data Mining
... the nearest neighbor ...the nearest neighbor algorithm, we will refer to some more recent ...works. k-Nearest Neighbor (kNN) is based on the principle that the instances ...
5
Comparison of supervised classifiers in the discrimin ation of preservation areas in a hydroelectric reservoir
... A manutenção de matas ciliares, considerada uma das práticas vegetativas de mitigação da de- gradação dos recursos hídricos, é exigida por lei. Contudo, no Brasil, ainda há uma progressiva e cons- tante descaracterização ...
16
The Importance of Feature Selection in Classification
... When comparing both the datasets by using K-Nearest Neighbor algorithm its clearly show that wine dataset is having more accuracy when compared to pima dataset. While testing and training dataset ...
6
Performance Evolution of Various Wavelets in Cervical Lesion Detection
... Cervical cancer is one of most common cancers among women in the world caused by human papilloma virus infection. It develops in the tissue of cervix which connects upper body of the uterus to the vagina. The types of ...
5
HITS: A History-Based Intelligent Transportation System
... In addition to the calculated measures, the HITS system also allows other moving object related queries to be computed. K-NEAREST NEIGHBOR (k-NN) and RANGE queries are both traffic related ...
13
Imbalanced multi-modal multi-label learning for subcellular localization prediction of human proteins with both single and multiple sites.
... a nearest neighbor algorithm for predicting the subcellular locations of proteins with multiple sites in budding ...ensemble k- nearest neighbor classifier, two algorithms called ...
10
Previsão de riscos de alagamentos e inundações com uso de inteligência artificial
... o k vizinhos mais próximos (k Nearest Neighbor – kNN), um clássico algoritmo de aprendizado de máquina, foi possível mostrar a viabilidade do uso de técnicas de inteligência artificial para a ...
13
Modeling of stem form and volume through machine learning
... algorithms: k nearest neighbor (k-NN), Random Forest (RF) and Artificial Neural Networks (ANN) for estimation of total volume and diameter to the relative ...
13
Data mining in HIV-AIDS surveillance system
... methodologies included multilayer artificial neural networks (MLP), naive bayesian classifiers (NB), support vector machines (SVM) and the k-nearest neighbor algorithm (KNN). The highest ...
15
Applying feature transformation using Relative Frequency with Power Transformation and Lemmatization in automatic Spam Filtering
... The k-nearest neighbor algorithm (k-NN) is a method for classifying objects based on closest training examples in the feature ...space. k-NN is a type of instance-based learning, or ...
7
An Efficient Bayesian Nearest Neighbor Search Using Marginal Object Weight Ranking Scheme in Spatial Databases
... Authentication codes offer message reliability within a symmetric key setting. It believe a strong attack circumstances where the opponent is adaptive and has right to use to authentication and verification of the data ...
6
TECHNICAL PAPER QUALITY OF A DIGITAL TERRAIN MODEL FOR SANTA CATARINA STATE
... ABSTRACT: Relief characterization using a digital terrain model (DTM) is widely applied in erosion, soil and vegetation modeling. However, factors, such as acquisition technology and the spatial resolution of the digital ...
11
Braz. J. Phys. vol.38 número3B
... Relations (6) and (12) define completely the algebra whose structural constants are the S-matrix of the spin- 3 2 model [21, 22, 30]. Since the several components of the wavefunction should be uniquely related, the above ...
5
Performance of young children on ''traveling salesperson'' navigation tasks presented on a touch screen.
... the nearest goal as the initial goal to ...the nearest-neighbor strategy, or the rule to select the next nearest point at each given ...
19
Hierarchical genetic clusters for phenotypic analysis
... furthest neighbor method, the nearest neighbor method, Ward’s method, and the median ...The nearest neighbor method was the most efficient in reconstructing the system of backcrossing, ...
10