the Nearest Neighbor Algorithm
An Improved Nearest Neighbor Algorithm for Solving TSP
... Traveling salesman problem is one of the most important mathematical concepts having very high socio economic impact. But since TSP is NP-complete, finding an optimal solution becomes very hard when problem size ...
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Evaluation Of The Performance Of K-Nearest Neighbor Algorithm In Determining Student Learning Styles
... K-Nearest Neighbor algorithm and Support Vector Machine with the purpose of finding a model that has the high performance of the new cases of the test ...K- Nearest Neighbor and Liner ...
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Performance Evaluation of SVM and K Nearest Neighbor Algorithm over Medical Data set
... k-nearest neighbor algorithm is a technique for classifying objects based on closest training examples in the problem ...k-nearest neighbor algorithm is amongst the simplest of ...
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GEO IP DETECTION OF CREDIT CARD FRAUD USING K-NEAREST NEIGHBOR ALGORITHM
... K-Nearest Neighbor algorithm in the fraud detection module in order to find the best method for detecting credit card fraud based on accuracy false positives and speed (computation ...
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Improve Adaptive k-Nearest Neighbor Algorithm using Multi-threading
... fewest nearest neighbors, k, approach infinity in this manner that M→∞, k→∞, the error rate of the kNN algorithm for the training set approaches the optimal Bayes error ...its nearest neighbor ...
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A Modified Rsa Algorithm For Security Enhancement And Redundant Messages Elimination Using K-Nearest Neighbor Algorithm
... k-Nearest Neighbor methods is to identify k samples in the training set whose independent variables x are similar to u , and to use these k samples to classify this new sample into a class, ...
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Analysis of Machine Learning Algorithms Performance for Real World Concept
... Bayes algorithm and 1-Nearest Neighbor algorithm were as ...Bayes algorithm for each subset were: ...1-NN algorithm regarding accuracies were: ...
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Provide Security of Ranked Multi keyword Search over Encrypted Data in cloud computing
... on security of cloud sourcing data for theunauthorized users. So that to provide security of cloud data the data owner will encrypt the data using segment encryption algorithm. After encrypting the data owner will ...
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Title: PERFORMANCE ANALYSIS OF HYBRID APPROACH OF K-NN ALGORITHM USING MULTIPLE-LEVEL LEARNING FOR TEXT CLASSIFICATION
... k-nearest-neighbor algorithm is a basic instance based learning method and widely used in similarity ...this algorithm is to classify a new dataset based on attributes and training ...k ...
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Presentation of a Parallel Algorithm for Nearest Neighbor Search on GPU Using CUDA
... that Algorithm‟s run on GPU with CUDA causes enhancement in it‟s ...explains Nearest Neighbor Algorithm in more detail and describes GPU and ...NN Algorithm is implemented in Parallel ...
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Real Time Location based Tracking using WIFI Signals
... Numerous algorithms are described in this research paper to track the users’ location with use of wireless WI-FI signals. The algorithms are such as: Bayesian Algorithm, History- based Algorithm, ...
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Prediction of Student’s Performance based on Incremental Learning
... and Nearest neighbor (KNN) have been ...that nearest neighbor algorithm gives better accuracy compared to others if applied on Student Evaluation dataset which has been ...
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Hybrid Algorithms of Whale optimization algorithm and k-nearest neighbor to Predict the liver disease
... K-Nearest neighbor (KNN) is a one of nonparametric classification techniques and it is able to process the information with continuous ...closest neighbor in order to determine the class of an ...
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Fast Nearest Neighbor Search With Keywords
... The R-trees allow us to remedy an awkwardness in the way NN queries are processed with an I-index. Recall that, to answer a query, currently we have to first get all the points carrying all the query words in Wq by ...
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Quick Search of the Nearest Neighbor with Words
... and nearest neighbor retrieval, involve only conditions on objects’ geometric ...a nearest neighbor query would instead ask for the restaurant that is the closest among those whose menus ...
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K Nearest Neighbor Based Missing Data Estimation Algorithm in Wireless Sensor Networks
... to algorithm LIN estimating the missing data according to the temporal correlation absolutely, its estimation error increases most when sampling time interval is ...multiple neighbor nodes to estimate the ...
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Optimal Clustering with Nearest Neighbor Relationships
... The HPC algorithm defines a search through the data space based on hubness as a kind of a local centrality estimate. To justify the use of the proposed stochastic scheme, we executed a series of initial tests on a ...
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A Logarithmic Complexity Algorithm for Nearest Neighbor Classification Using Layered Range Trees
... compared to n if brute force was used. To test the performance of the algorithm and see how large k is on average for every dimension, we performed two tests. The first was done on randomly generated datasets for ...
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The Detection of Electrical and Electronics Components using K nearest Neighbor (KNN) classification Algorithm
... This project has a simple electronic component detection procedure which has three major steps; firstly the objects are being recognized based on its physical appearances via length, Bre[r] ...
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FAST NEAREST NEIGHBOR SEARCH WITH KEYWORDS
... Existing works mainly focus on finding top-k nearest Neighbors, where each node has to match the whole Querying keywords .It does not consider the density of data objects in the spatial space. Also these methods ...
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