k-nearest neighbour algorithm
A K-Nearest Neighbour Algorithm-Based Recommender System for the Dynamic Selection of Elective Undergraduate Courses
... the k-nearest Neighbour algorithm to discover hidden relationships between the related courses passed by students in the past and the currently available elective ...
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A Review of Data Classification Using K-Nearest Neighbour Algorithm
... in Nearest Neighbor Classification is quite simple, examples are classified based on the class of their nearest ...The k - nearest neighbor classifier is a conventional nonparametric ...
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Discretisation of Data in a Binary Neural k-Nearest Neighbour Algorithm
... a k-Nearest Neighbour predictor. Our k-NN is constructed using binary neural networks which require continuous-valued data to be discretised to allow it to be mapped to the binary neural ...
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Identifying Lung Cancer Using X-Ray: A Review
... Genetic algorithm, K-nearest neighbour algorithm, Decision tree algorithm, Multilayer perceptron algorithm and various other techniques like MAD(Median Absolute Deviation) ...
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A Study on Content Based Image Retrieval System using K-NN Algorithm and Mobile Agents
... lazy algorithm which means it does not use the training data points to any generalization we can also say that, there is no explicit training phase or it is very ...that K-NN keeps all the training ...
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Diabetes Diagnosis using Machine Learning Algorithms
... Diabetes is the third leading cause of death following diseases of heart and cancer. But with the rise of Machine Learning approaches we have the ability to find a solution to this issue. The aim of Machine Learning and ...
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... India is an agricultural country and its economy is largely based upon crop productivity. For analyzing the crop productivity, rainfall prediction is require and necessary. Rainfall Prediction is the application of ...
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A Comparison of Multiple Algorithms for Fingerprinting using IEEE802.11
... To collect data with the mobile phones it was developed an application for the Android platform (Fig. 5). Since the objective of this application is to collect data to test the different LEA and to fine tune the weights ...
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Real Time Sentiment Classification of Tweets using Linear (LDA) & Nonlinear (Cart and KNN) Algorithms
... linear algorithm as LDA (Linear Discriminant Analysis) and nonlinear KNN (K Nearest Neighbour) and CART (Classification and Regression Tree) algorithm for classifying the tweets text ...
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A Review on Plant Texture Analysis Using Leaf Images
... the Algorithm of MMC, classification stage and the Data preprocessing for application of the ...the nearest neighbour (1NN) and kNN classifiers, it can be found that the MMC classifier can not ...
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PERFORMANCE ANALYSIS OF DENSITY ESTIMATION AND MASS ESTIMATION Khushabu Trivedi 1, Parvati Bhurani2
... and k-nearest neighbour density estimator have high time and space complexities The Bayesian algorithm totally dependent on density estimation for the base modelling so all the algorithms ...
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Prediction of Individual Student Job Placement on the Basis of Last Year Statistics in Exam and Online Test
... various algorithm techniques such as Support vector machine, Random forest, K nearest neighbour, Gaussian Noise, Logistic Regression and Decision ...
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Probabilistic Classification from a K Nearest Neighbour Classifier
... The experiments introduced in this paper were con- ducted on a workstation using the Microsoft Windows XP operating system with a 3.2 GHz processor and 3 GB of RAM; the algorithm was implemented in the MAT- LAB ...
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Human Object Behavior Monitoring System based on Machine Learning Algorithm
... K-Nearest Neighbour is one of the machine learning ...learning algorithm. The training process of this algorithm consists of storing feature vectors and labels of the training ...the ...
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Experience with Rule Induction and k Nearest Neighbour Methods for Interface Agents that Learn
... Abstract—Interface agents are being developed to assist users with a variety of tasks. To perform effectively, such agents need knowledge of user preferences. An agent architecture has been developed which observes a ...
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Prediction Using Back Propagation and k-Nearest Neighbour (k-NN) Algorithm
... ABSTRCT: Prediction of Stock Prices is not only inquisitiveness but also the very challenging topic. This paper intension is predict stock prices for sample of some major companies using back propagation and ...
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Title: An Enhanced Model for the Classification of Mined Data
... both K-Nearest Neighbour (KNN) Algorithm and Euclidean Distance Classifier for text mining and classification using data mining that requires fewer documents for ...
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Artificial immune system based on real valued negative selection algorithms for anomaly detection
... Selection Algorithm proposition as shown in Figure ...Selection Algorithm that uses real-valued representation of the self/non-self ...This algorithm, called Real-Valued Negative Selection (RNSA), ...
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Location And Query Privacy In K Nearest Neighbour Queries
... the k nearest neighbors (kNN) queries where the mobile user queries the LBS provider on k closest ...the nearest k POIs by comparing the distances between the mobile user's location and ...
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A binary neural k-nearest neighbour technique
... AURA k-NN detailed in (Weeks et ...AURA k-NN is 97% for the REAL data set and 99% for the IBM data set when the first 25 nearest neighbours are ...50 nearest neighbours are compared and 84% ...
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