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Bayes decision

Error Measures and Bayes Decision Rules Revisited with Applications to POS Tagging

Error Measures and Bayes Decision Rules Revisited with Applications to POS Tagging

... statistical decision theory and try to minimize the average risk or loss in taking a ...as Bayes decision rule (Chapter 2 in (Duda and Hart, ...

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A Survey on Prediction of Diabetes Using Data Mining Technique

A Survey on Prediction of Diabetes Using Data Mining Technique

... Data Mining is used to invent knowledge out of data and exhibiting it in a condition that is easily understandable to humans. It is a process to inspect large amounts of data collected. Information technology plays a ...

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Usage of Data Mining Techniques in Predicting the Heart Diseases Decision Tree & Random Forest Algorithm

Usage of Data Mining Techniques in Predicting the Heart Diseases Decision Tree & Random Forest Algorithm

... Naïve Bayes, Neural network, Kernel density, automatically defined groups, bagging algorithm and support vector machine showing different levels of accuracy on multiple databases of patients at different ...of ...

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Comparison of supervised machine learning classification techniques in prediction of locoregional recurrences in early oral tongue cancer

Comparison of supervised machine learning classification techniques in prediction of locoregional recurrences in early oral tongue cancer

... phase, decision forest showed the highest accuracy while naive Bayes and decision forest showed the best area under receiving operating characteristic (AUC of ...naive Bayes, decision ...

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ISSN (Online) 2347-3207 A Comparative Study of Classification Methods in Data Mining using RapidMiner Studio

ISSN (Online) 2347-3207 A Comparative Study of Classification Methods in Data Mining using RapidMiner Studio

... Naive Bayes, Decision Stump and Rule Induction performed average, but for the KNN and Decision Tree the accuracy is ...Naive Bayes, Decision Tree and Rule Induction performed well, and ...

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Predictive Models for Post-Operative Life Expectancy after Thoracic Surgery

Predictive Models for Post-Operative Life Expectancy after Thoracic Surgery

... naive Bayes, decision trees, and support vector ...naive Bayes nor decision trees proved up to the task of classifying this particular dataset with a high accuracy, it is also probable that ...

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ABSTRACT: Word sense disambiguation is solved with the help of various data mining approaches like Naïve Bayes

ABSTRACT: Word sense disambiguation is solved with the help of various data mining approaches like Naïve Bayes

... Disambiguation is performed in this paper via a four supervised approaches, using WordNet and Senseval-3. Table (1), shows the results of four approaches, Naïve Bayes, Decision tree,, Decision List, ...

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Traffic Data Analysis using Decision Tree and Naïve Bayes Classifier

Traffic Data Analysis using Decision Tree and Naïve Bayes Classifier

... leading causes of death worldwide. The Classification and Characterization for the algorithms are essential for these traffic . Data mining techniques have been used in real time applications due to its artificial ...

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Application of Machine Learning in Predicting Ovarian Cancer Survivability

Application of Machine Learning in Predicting Ovarian Cancer Survivability

... single decision tree (SDT), boosted decision tree (BDT) and decision tree forest (DTF) for the detection of breast cancer during validation phase of analysis DTF achieved ...Naive Bayes, ...

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A NOVEL EARLY WARNING SYSTEM USING FUZZY MULTIPLE ATTRIBUTE DECISION MAKING 
ALGORITHM AND METEOROLOGICAL DATA

A NOVEL EARLY WARNING SYSTEM USING FUZZY MULTIPLE ATTRIBUTE DECISION MAKING ALGORITHM AND METEOROLOGICAL DATA

... This paper reports our research effort aimed at systematically reviewing and analyzing malware prediction techniques, threats, tools and datasets. Malware is the primary choice of weapon to carry out malicious intents in ...

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Probabilistic decision making with spikes: From ISI distributions to behaviour via information gain

Probabilistic decision making with spikes: From ISI distributions to behaviour via information gain

... for decision making like s-MSPRT, at the behavioural level? Our starting point for this analysis is the obser- vation that the mean decision sample size (mean decision sample for short) of our ...

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Emergency decision model of coalmine sudden gas events based on bayes theory

Emergency decision model of coalmine sudden gas events based on bayes theory

... gas disasters, adjust response options of emergency plans to make scientific decisions according to analysis and predictions of dynamic changes in uncertainty consequence of specific disasters have been key issues of ...

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Hybrid Decision Tree and Naïve Bayes Classifier for Predicting Study Period and Predicate of Student’s Graduation

Hybrid Decision Tree and Naïve Bayes Classifier for Predicting Study Period and Predicate of Student’s Graduation

... hybrid decision tree and naïve bayes classifier to predict the study period and predicate of ...of decision tree C4.5 algorithm and naive bayes classifier with data partition 70%, 80% and ...

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Scaling Up the Accuracy of Decision-Tree Classifiers: A Naive-Bayes Combination

Scaling Up the Accuracy of Decision-Tree Classifiers: A Naive-Bayes Combination

... a decision tree can be expressed recursively ...a decision tree has been built, it classify a test instance by sorting it down the tree from the root node to one leaf node, which provides the classification ...

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A New Cygnus Optimization Algorithm for Prediction Of Cardio Vascular Disease 

A New Cygnus Optimization Algorithm for Prediction Of Cardio Vascular Disease 

... J48 Decision Tree, Naive Bayes and Neural Network on the prediction of Cardio-Vascular ...Naïve Bayes with various filtering analysis in order to build a network intrusion detection ...Naïve ...

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Analysis and Prediction of Heart Disease Using Decision Tree and Naive Bayes

Analysis and Prediction of Heart Disease Using Decision Tree and Naive Bayes

... The current framework utilizes the decision tree system . These are non-parametric learning method utilized for characterization. And it is the one of most powerful techniques in classification .It constructs the ...

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Enhancing Machine Based Spam Detection Using Twitter

Enhancing Machine Based Spam Detection Using Twitter

... Symbiotic Data Mining is a distributed data mining approach that unifies the content-based filtering with collaborative filtering described in [7]. The main objective is to reuse local filters to improve personalized ...

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An Iterative Decision Rule to minimize cost of Acceptance Sampling Plan in Machine Replacement Problem

An Iterative Decision Rule to minimize cost of Acceptance Sampling Plan in Machine Replacement Problem

... Many approaches have been proposed for the problem of machine replacement but analyzing the machine based on quality of produced items is not widely addressed [13]. In a paper, Fallahnezhad and Niaki employed control ...

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Sentimental Analysis of Flipkart reviews using Naïve Bayes and Decision Tree algorithm

Sentimental Analysis of Flipkart reviews using Naïve Bayes and Decision Tree algorithm

... Abstract— The e-commerce is developing rapidly these years, buying products on-line has become more and more fashionable owing to its variety of options, low cost value (high discounts) and quick supply systems, so ...

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Network Intrusion Detection Using Supervised Machine Learning Technique

Network Intrusion Detection Using Supervised Machine Learning Technique

... C4.5 decision tree and NavieBayes is applied on the training dataset and the implementation of the algorithm is done using spyder ...C4.5 decision is more efficient in detection of DDOS attack ...

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