Classification Algorithm
Diabetes data prediction using data classification algorithm
... The very dangerous disease in medicinal field is diabetes disease which is affected for many peoples in popular countries like India. The diagnosis of diabetes is a tedious process. So with improvement in science and ...
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A Classification Algorithm to Improve the Design of Websites
... Measuring the quality of the classification algorithm in navigation patterns mining systems needs to characterize the quality of the results obtained. The experimental evaluation was conduced using Azad ...
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Weight based Classification Algorithm for Medical Data
... which classification provides the clear decisions for medical domain ...new classification algorithm is designed and compared with support vector machine, ...developed classification ...
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Hierarchical Classification Algorithm Based on FastText
... common algorithm for text classification, generally, the traditional machine learning classification algorithm is applied to the CLC ...hierarchical classification model earlier in the ...
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Analytical Research on Decision Tree Algorithm and Naive Bayesian Classification Algorithm for Data Mining
... The paper presents an extensive modification of ID3 (Iterative Dichotomiser) algorithm and Naïve Bayesian Classification algorithm for data mining. The automated, prospective analyses offered by data ...
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Study Of Classification Algorithm For Lung Cancer Prediction
... mining classification techniques and it is found that the Naive Bayes algorithmgives a better performance over the other classification algorithm such as Bayesian and ...
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Flower Grain Image Classification Using Supervised Classification Algorithm
... Our proposed system is identified flower pollen grain and classifies them into different classes. We have used colour and texture parameters to extract the features of pollen grains. ANN feed forward classifier is used ...
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Classification Algorithm Based on Nodes Similarity for MANETs
... The classification is an essential task for data analysis and interpretation. It is used to divide a set of data into groups or clusters. An item is characterized by a high simi- larity to components of its group, ...
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PLANT LEAF CLASSIFICATION USING SUPERVISED CLASSIFICATION ALGORITHM
... forward algorithm to classify our plant leaf images and also compare NN with SVM ...achieved classification accuracy of ...of classification is checked using color feature and texture features ...
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Efficient Handwritten Digit Classification using User-defined Classification Algorithm
... The novelty of this method is that, free from size normalization, fast, accurate, independent of size and Writer style/ink independent. The present paper defined classification of isolated handwritten digits with ...
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A Supervised Classification Algorithm for Note Onset Detection
... An in-depth analysis of model errors on the annotated “Ball- room” dataset shows that most of the false negatives are pro- duced by pitched onsets with thin harmonics. This is sur- prising because such onsets are easily ...
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Improved J48 Classification Algorithm for the Prediction of Diabetes
... C4.5 classification techniques have achieved the maximum accuracy of 100% in classifying 45 images from the Gold Standard ...learning classification model using both historical binary ratings and external ...
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Improving the cAnt-MinerPB Classification Algorithm
... This process can be implemented adding only a few lines to the algorithm presented in Figure 1. The first addition would be the creation of a rule qual- ity functions graph and initialise its pheromones (line 1). ...
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A New Class Based Associative Classification Algorithm
... associative classification, a new class based frequent pattern mining strategic is designed in CACA to cut down the searching space of frequent ...associative classification but help to guide the rule ...
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A Text Classification Algorithm Based on PCA
... and classification, although the original word feature-document matrix A has higher dimension, However, due to the sparsity of the matrix A, after PCA in keep more than 95% under the premise of information for ...
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“Evaluating Performance of Data Mining Classification Algorithm in Weka”
... Input data is an important part of data mining applications. The data used in my experiment is real world data obtained from http://www.technologyforge.net/Datasets/ [9], during evaluation multiple data sizes were used, ...
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Opinion classification system using supervised learning algorithm
... Opinion Mining is the technique of detecting and extracting subjective information in text documents (Bhatia et al., 2015). Kaiser et al. (2009) focuses on mining relationships in online communication. The relationships ...
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Inclusion of Efficient Rules in PRISM Algorithm for Data Classification
... Data classification is the process of classify data into different types, forms or any other separate ...data classification is a regulatory requirement, as data must be searchable and recoverable within ...
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A Boosting Algorithm for Classification of Semi Structured Text
... learning algorithm that can automatically capture relevant structural information observed in text, rather than to heuristically add this informa- tion as new ...a classification algorithm that cap- ...
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Mushroom Classification Using ANN and ANFIS Algorithm
... different classification algorithm such as ANN, ANFIS , and Bayes Net classifier were compared on the basis of Mean absolute error, Accuracy, Kappa statistic for mushroom ...
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