nearest-neighbor classification framework
Exact fuzzy k Nearest neighbor classification for big datasets
... The MapReduce model defines three stages to manage distributed data: Map, Shuffle and Reduce. The first one reads the raw data in form of <key-value> pairs, and it distributes through several nodes for parallel ...
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Rate of Convergence of $k$-Nearest-Neighbor Classification Rule
... Chaudhuri and Dasgupta (2014) distribution-dependent rates of convergence are provided for the nearest neighbor classification rule in the framework of metric spaces. Therein a smoothness ...
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Distance Metric Learning for Large Margin Nearest Neighbor Classification
... k-nearest neighbor (kNN) classification depends significantly on the metric used to compute distances between different ...kNN classification from labeled ...kNN classification using ...
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Empirical Study of Image Classification Techniques to Classify the Image using SVM: A Review
... of classification, data collection, image pre-processing steps and feature extraction ...rule classification technique for ...complete classification process including “image acquisition, image ...
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Nearest Neighbor Voting in High Dimensional Data: Learning from Past Occurrences
... to nearest-neighbor ...bor classification. We argue that some of the neighbor occurrences carry more information than others, by the virtue of being less frequent ...k-Nearest ...
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K-Nearest Neighbor Classification Mechanism of Secure Encrypted Relational Data
... We propelled the PPKNN over scrambled information to accomplish economies of scale for Cloud Computing. At that point we presented new security primitives, specifically secure least (SMIN), secure recurrence (SF), and ...
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An Ensemble of Classifiers using Dynamic Method on Ambiguous Data
... are uncorrelated and diverse as much as possible. The objectives of proposed work are containing an Analysis and Design of Weighted Instance Selection technique for k-NN (K-Nearest Neighbor) Classifiers. It ...
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An Augmentation of Data Collection Functioning With Implementation by Pattern Variation Discovery in Wireless Sensor Networks: Novel Overview with Applications
... Khushboo Sharma, Manisha Rajpoot and Lokesh Kumar Sharma in “Nearest Neighbor Classification for Wireless Sensor Data” Has used a Nearest Neighbor Classification te[r] ...
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Role of Big Data in Imaging Modalities to Classify the Image Using SVM
... of classification, data collection, image pre- processing steps and feature extraction ...rule classification technique for ...complete classification process including image acquisition, image ...
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William_Wiener_Biology_Honors_Thesis.pdf
... their nearest neighbors (Evangelista et. al, 2017). Nearest neighbor distance appeared to help predict whether swifts were cooperating, with the conclusion being that local interactions were ...
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A Logarithmic Complexity Algorithm for Nearest Neighbor Classification Using Layered Range Trees
... In a dataset, instances with d attributes could be looked at as points in d dimensional space. When searching for near- est neighbors to a query point q, it would be effective if we could search only points that surround ...
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A Dependent Multilabel Classification Method Derived from the k-Nearest Neighbor Rule
... In this paper, we present a generalization of the MLkNN- based approach to multilabel classification problems where the dependencies between classes are considered. We call this method DMLkNN, for dependent ...
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K Nearest Neighbor Classification Approach for Face and Fingerprint at Feature Level Fusion
... Biometric system that based on single biometric called uni- modal biometrics usually suffers from problems like imposter’s attack or hacking, unacceptable error rate and low performance. So the need of using multimodal ...
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EFFICIENT CLASSIFICATION METHOD FOR LARGE DATASET BY ASSIGNING THE KEY VALUE IN CLUSTERING
... KDDCUP99 dataset contains around 4,900,000 simulated network records with 41 attributes (34 continuous attributes and 7 categorical attributes). These records fell in normal or one of the following four categories ...
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Support Vector Machine versus k-Nearest Neighbor for Arabic Text Classification
... k nearest neighbors among the pre- classified training documents based on some similarity measure, and ranks those k neighbors based on their similarity scores, the categories of the k nearest neighbors are ...
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Text Classification and Classifiers: A Comparative Study
... text classification is feature selection [7] to construct vector space, which improves the accuracy of a text ...text classification a major problem is the high dimensionality of the feature ...
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Optimal Clustering with Nearest Neighbor Relationships
... number of k-occurrences of point x D, i.e., the number of times x occurs in k-nearest neighbor lists of other points from D. As the dimensionality of data increases, the distribution of k-occurrences ...
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FAST NEAREST NEIGHBOR SEARCH WITH KEYWORDS
... and nearest neighbor retrieval, involve solely conditions on objects’ geometric ...a nearest neighbor query would instead invite the restaurant that is the nearest among those whose ...
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Development of an Intelligent Virtual Grader for Estimation of Fruit Quality
... color classification, extraction of useful information concerning the spectral properties of object by discovering the best match from a set of known descriptors or class models to implement the recognition task ...
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Quick Search of the Nearest Neighbor with Words
... It is until recently that attention was diverted to multidimensional data. The best method to date for nearest neighbor search with keywords is due to Felipe et al.. They nicely integrate two well-known ...
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