k nearest neighbors method
Pattern Recognition Using K-Nearest Neighbors (KNN) Technique
... Artificial intelligence is the intelligence of machines and the branch of computer science which aims to create it .AI is defined as the study and design of intelligent agents where an intelligent agent is a system that ...
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Simulation of Agricultural Logistic Processes with k-Nearest Neighbors Algorithm
... further method of modelling is the k-Nearest Neighbors Method ...classification method which is one of the simplest (Altman, 1992) and at the same time oldest (Cover, ...
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Comparative Study for Text Document Classification Using Different Machine Learning Algorithms
... Classification is a supervised learning method: the goal is finding the labels of the unknown object. In the real world, the tedious amounts of manual works are required to label the unknown documents. The system ...
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Fast and Scalable Approaches to Accelerate the Fuzzy k Nearest Neighbors Classifier for Big Data
... This section presents two approximate and distributed pro- posals for the FkNN algorithm based on the HS method to address big data problems implemented in Spark. Two different approaches are proposed in the class ...
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Distance Based Method for Outlier Detection of Body Sensor Networks
... previous method may have a poor ...to k nearest neighbors for a diagnosed sliding window with the estimated KDE, if this probability is less than a threshold, then we decide that there are ...
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Find the Nearest Hotels on Google Map Using IR2-tree & Spatial inverted index
... fast nearest neighbor search using ...top-k Nearest Neighbors, where each node has to match the whole querying keywords ...for nearest restaurant, instead of considering all the ...
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Improving Convolutional Neural Networks’ Accuracy in Noisy Environments Using k-Nearest Neighbors
... hybrid method that replaces the softmax layer by a kNN classifier in the inference stage without modifying the training ...of neighbors is higher in larger datasets; therefore, the proposed method ...
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Local K-Nearest Neighbors Model using Z-Order R-Tree for Big Data
... approximate nearest neighbors rather than the exact ...quantization method for approximate nearest neighbors (ANN) search which enables faster and more accurate retrieval on publicly ...
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Title: WHO ARE the LIKELIEST SURVIVORS of BREAST CANCER- An ANALYSIS by K NEAREST NEIGHBORS ALGORITHM
... Several ensemble procedures are available in data mining literature for analysis purpose. Of these, boosting method [7] will be applied in this study. In boosting procedure, at first a base classifier is prepared ...
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EFFECT OF DISCRETIZATION METHOD ON THE DIAGNOSIS OF PARKINSON S DISEASE
... tion method is used as the discretization method, and support vector machines, ...C4.5, k-nearest neighbors and Na¨ıve Bayes are used as the classification ...discretization ...
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An Evaluation ofDetection of Outliersby Reverse Nearest Neighbors Method
... of k nearest neighbor ofinstance and local density of data instance itself then datainstance is considered to be normal and not as an ...of k [5], i.e. k nearest neighbor and volumeof ...
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Detection Model for Daniel of Service Attacks using Random Forest and k Nearest Neighbors
... Chen et al. [24] conducted wrapper-based feature selection algorithm aiming at modeling lightweight IDSs. They used Modified Random Mutation Hill Climbing (MRMHC) as search strategy to specify a candidate subset for ...
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k-Nearest Neighbors Queries in Time-Dependent Road Networks
... We also propose an access method that facilitates the processing of TD-NE-A ∗ in secondary storage, for cases of larger networks. Before explaining it, we would like to draw attention to some points that do not ...
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A novel method for the detection of R peaks in ECG based on K Nearest Neighbors and Particle Swarm Optimization
... [29], k-means [30], empirical mode decomposition (EMD) [31], geometrical matching [32–34], combined threshold method [35, 36], phase space method [37], Hilbert Transform method [38], and mixed ...
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A Completion on Fruit Recognition System Using K Nearest Neighbors Algorithm
... analysis method like color-based, shaped-based, size-based and ...analysis method shape, size and color, texture based method to increase accuracy of ...Proposed method used is nearest ...
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An Efficient movie recommendation algorithm based on improved k-clique
... this method gives the most accurate ...the k‑clique methodology used to analyze social networks to be the guidance of this ...improved k‑clique methods which are the best accuracy of the ...
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Adapted K-Nearest Neighbors for Detecting Anomalies on Spatio–Temporal Traffic Flow
... problem of mining sequential patterns in semantic trajecto- ries, leveraging a new method named SPLITTER to discover fined-grained sequential patterns. Yuan et al. [35] address the problem of discovering regions ...
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The Performance of K Nearest Neighbors on Malignant and Benign Classes: Sensitivity, Specificity, and Accuracy Analysis for Breast Cancer Diagnosis
... Breast cancer is one of the major threats to women nowadays. Early detection of breast cancer decreases mortality rate. Machine learning algorithms are used for this purpose. Accuracy is the most popular measure for ...
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On Secured Blockchain Technology For K Nearest Neighbors Algorithm
... the gathering of security organizations are as indicated by the going with: Confidentiality: guarantees that the records in a PC machine and transmitted data are available handiest for investigating by method for ...
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Breast Cancer Diagnosis by using k Nearest Neighbor with Different Distances and Classification Rules
... Cancer diagnosis is one of the most studied problems in the med- ical domain. Several researchers have focused in order to improve performance and achieve to obtain satisfactory results. Breast can- cer is one of cancer ...
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