[PDF] Top 20 Breast Cancer Data Classification Using SVM and Naïve Bayes Techniques
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Breast Cancer Data Classification Using SVM and Naïve Bayes Techniques
... ABSTRACT: Breast cancer is one of the major problems for women that have increased over ...in cancer society is “Early detection means better chances of ...prevent breast cancer with ... See full document
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Title: A NEW HYBRID APPROACH FOR NETWORK TRAFFIC CLASSIFICATION USING SVM AND NAÏVE BAYES ALGORITHM
... traffic data and assign any testing flow to the application-based class of its nearest ...clusters using the expectation maximization (EM) algorithm and manually label each cluster to an ...applications ... See full document
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Classification and Stage Prediction of Lung Cancer using Convolutional Neural Networks
... Lung cancer is a type of cancer that begins in the ...Lung cancer is the leading cause of cancer deaths in the United States, among both men and ...Lung cancer claims more lives each ... See full document
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Predicting Diabetes Mellitus using Data Mining Techniques
... diabetes. Data mining approach helps to diagnose patient’s ...diabetes using data mining ...the data mining techniques in ...models using 9 input variables and one output ... See full document
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Prognosis of Heart Disease using Data Mining Techniques: A Comprehensive Survey
... used SVM and ANN techniques for classification and prediction of disease ...sets. SVM and ANN were used to arrange the datasets into two ...the SVM classification are compared to ... See full document
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Comparison of Classification Models for Breast Cancer Identification using Google Colab
... Abstract: Classification algorithms are very widely used algorithms for the study of various categories of data located in multiple databases that have real-world ...of classification algorithms in ... See full document
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Detecting Breast Cancer by using Mammography Microcalcification
... Naïve Bayes is a machine learning algorithm for classification ...theorem. Naïve Bayes is basically used for the purpose of the classification of text which involves training ... See full document
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Drug Consumption Risk Analysis
... collected data on drug addiction levels of individuals based on their personality ...pre-processing techniques to avoid false results. After pre-processing, the data would be free from errors and ... See full document
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A Review of Different Classification Techniques in Machine Learning using Weka for Plant Disease Detection
... analyzing data from different aspects and summarizing it into valuable ...analyze data from different dimensions, categorize and the relationships are ...a data analysis tool for machine learning ... See full document
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Title: SENTIMENT ANALYSIS USING SVM AND NAÏVE BAYES ALGORITHM
... the data reveals is merely one reason behind the emerge of interest in new systems that deal directly with opinions as a first-class ...sentiment classification, feature based Sentiment ... See full document
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Cost-sensitive Naïve Bayes Classification of Uncertain Data
... the naïve Bayes based algorithms overcome these difficulties more ...a Naïve Bayes based Classification to handle Cost-sensitive learning on Uncertain ... See full document
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Analysis The Sentiments Of Amazon Reviews Dataset By Using Linear SVC And Voting Classifier
... the data between preparation and assessments by splitting the data collection between 90% or ...of data collection would be ...the classification algorithm and get the ...Voting ... See full document
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Classification and Prediction of Dermatitis Dataset using Naïve Bayes and Value Weighted Naïve Bayes Algorithms
... dermatology Data directly taken from the source will likely have inconsistencies, errors or most importantly, it is not ready to be considered for a data mining ...of data in recent science, industry ... See full document
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Performance Analysis of Data Mining Classification Techniques
... 3. K-nearest neighbors: It is an instance-based classifier. It operates on the premises that classification of unknown instances can be done by relating the unknown to the known according to some distance or ... See full document
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Title: NAIVE BAYES CLASSIFIER WITH MODIFIED SMOOTHING TECHNIQUES FOR BETTER SPAM CLASSIFICATION
... “Automated Classification of Naïve Bayesian Algorithm”, Proceedings of international Multi-Conference of Engineers and Computer Scientists, Volume1, March 2012, ...Multinomial Naïve Baye s ... See full document
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FACTORS AFFECTING IS SUCCESS AND TECHNOLOGY ACCEPTANCE: A CASE STUDY
... Bag of Words is a model that represents objects globally such as text or documents as a word (multiset) word regardless of grammar and even word order to preserve its diversity [16]. Bag of Words is a common method used ... See full document
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Comparative Analysis of Data Mining Techniques for Malaysian Rainfall Prediction
... [1]. Data mining aims to extract useful knowledge and represent the new knowledge to make it ...time-series data mining. Time-series data mining is the process of analyzing the sequence of ... See full document
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PREDICTION OF CORONARY ARTERY DISEASE USING GENETIC ALGORITHM BASED FEATURE SELECTION AND RANDOM FOREST CLASSIFIER
... Coronary Artery Disease (CAD) is one of the most prevalent diseases, which can lead to disability and sometimes even death. Diagnostic procedures of CAD are typically invasive, although they do not satisfy the required ... See full document
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The Prediction of Heart Disease using Naive Bayes Classifier
... In Classification Algorithm the main objective is to predict the target class by analysing the training dataset ...medicinal data, so as to help clinicians in improving their conclusion for the treatment ... See full document
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Machine Learning Techniques Used for the Detection and Analysis of Modern Types of DDoS Attacks
... learning techniques to identify the command and control traffic of IRC-based botnets (compromised hosts that are collectively commanded using Internet Relay Chat ...naive Bayes, and Bayesian network ... See full document
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