[PDF] Top 20 Study of Decision Tree Classification Algorithms using Matrimonial System
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Study of Decision Tree Classification Algorithms using Matrimonial System
... simple decision tree learning algorithm introduced in 1986 by Quinlan ...the decision tree by employing a top-down, greedy search through the given sets to test each attribute at every ... See full document
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A Comparative Study of Machine Learning Algorithms and Their Ensembles for Botnet Detection
... tion System. Although such system has been applying various machine learn- ing techniques, comparison of machine algorithms including their ensembles on botnet detection has not been figured ...this ... See full document
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Comparison Of Datamining Techniques For Prediction Of Breast Cancer
... selected using Information Gain and ...disease using classification algorithms. This study focus on studying the performance of six different classifiers, which gives high accuracy in ... See full document
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IJCSMC, Vol. 5, Issue. 5, May 2016, pg.483 – 488 A Survey on Classification Techniques in Data Mining for Analyzing Liver Disease Disorder
... his study, he compensate the insufficiency of liver disease disorder data usefully, he said a method based oversampling in minor ...classes. Decision tree algorithm does not give high priority for ... See full document
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Analysis and classification of heart diseases using heartbeat features and machine learning algorithms
... This study proposed an ECG (Electrocardiogram) classification approach using machine learning based on several ECG ...implemented using ML-libs and Scala language on Apache Spark framework; ... See full document
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Appraisal of the Classification Technique in Data Mining of Student Performance using J48 Decision Tree, K Nearest Neighbor and Multilayer Perceptron Algorithms
... This study uses the classification techniques of data mining to mine data of Computer Science students of Kwame Nkurmah University of Science and Technology, Kumasi, Ghana to ascertain if there is any ... See full document
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Diabetic Foot Risk Classification using Decision Tree and Bio Inspired Evolutionary Algorithms
... This classification enables the podiatrists to identify people at risk and ensure proper assessment at regular intervals to prevent ...risk classification system that assesses the foot of patient ... See full document
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Decision support methods in diabetic patient management by insulin administration neural network vs induction methods for knowledge classification
... of decision tree learning algorithms as well as neural networks for knowledge classification which is further used for decision support, this paper examines their relative merits by ... See full document
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Accuracies and Training Times of Data Mining Classification Algorithms: An Empirical Comparative Study
... mining algorithms are accuracy of classification/ prediction and time taken for ...best algorithms for classification/prediction tasks in data ...this study was designed to determine ... See full document
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Marketing Data Mining Classifiers: Criteria Selection Issues in Customer Segmentation
... In this study, we implemented the most common classification methods for customer segmentation as decision tree algorithms, K-nearest neighbor, Logistic regression, Naïve Bayesian, assoc[r] ... See full document
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Machine Learning Approach for Bottom 40 Percent Households (B40) Poverty Classification
... predictive classification is important to help the government to identify and develop specific actions by engaging further consultations with relevant stakeholders, which include ministries, academia and civil ... See full document
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A Data Mining System for Predicting University Students’ Graduation Grades Using ID3 Decision Tree Algorithm
... A study was conducted on the prediction of students’ graduation grades using the ID3 decision tree algorithm with data such as the grade in secondary school, entrance examination score and the ... See full document
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Health Prediction System by using Data Mining
... mining algorithms for predicting survival of CHD patients based on 1000 cases ...mining algorithms to develop the prediction models using the 502 ...the decision trees models came out to be ... See full document
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Sentiment Analysis of Movie Reviews using Machine Learning Techniques
... paper. Study of frequently used classification algorithms such as Naïve Bayes, Random Forest, k-nearest neighbour, Decision Tree Induction, Support Vector Machine was ...tool ... See full document
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AN APPROACH FOR FEATURES MATCHING BETWEEN BILATERAL IMAGES OF STEREO VISION SYSTEM APPLIED FOR AUTOMATED HETEROGENEOUS PLATOON
... Firstly, decision trees are known as highly efficient tools of machine learning and data mining, capable to produce accurate and easy-to-understand ...two algorithms in order to obtain a very efficient ... See full document
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Student Result Analysis System and Predicting Difficulty Level of Subject
... multiclass classification refers to the classification of the instance into more than two ...Multiclass classification and prediction is suitable for hand written digit recognition, hand written ... See full document
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A Hybrid Classification Model For Diabetes Dataset Using Decision Tree
... The study proposes to use the UCI repository dataset called PIMA Indians Diabetes dataset and decision tree algorithms like ...FB Tree. The comparison study includes parameters ... See full document
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AN OPTIMISED INTELLECTUAL AGENT BASED SECURE DECISION SYSTEM FOR HEALTH CARE
... are classification and prediction. Classification models predict categorical labels (discrete, unordered) while prediction models predict continuous-valued ...functions. Decision Trees and Neural ... See full document
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A Novel Technique for Weed Detection using Textural Similarities
... this study used an imaging spectrometer system, which supports micro-scale plant feature analysis by acquiring high-resolution hyper spectral images of corn and a number of weed species in the ... See full document
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IJCSMC, Vol. 6, Issue. 8, August 2017, pg.49 – 54 A COMPARATIVE STUDY OF DIAGNOSING LIVER DISORDER DISEASE USING CLASSIFICATION ALGORITHM
... The study surveyed some data mining techniques to predict the liver disease at earlier ...The study analyzed algorithms such as C4.5, Naive Bayes, Decision Tree, Support Vector Machine, ... See full document
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