Performance of the decision tree models
Evaluating performance of meta-heuristic algorithms and decision tree models in simulating water level variations of dams’ piezometers
... PSO algorithm was created by Kennedy & Eberhart [26] based on the collective movement of birds or a group of fish. PSO is an optimization sample capable to model the human population for processing the science, which ...
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Diagnosis of Breast Cancer using Decision Tree Models and SVM
... with decision trees is popular and effective data mining classification ...approach. Decision trees have the ability to generate understandable classification rules, which are very efficient tool for ...
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ASSESSING DECISION TREE MODELS FOR CLINICAL IN VITRO FERTILIZATION DATA
... C5.0 decision tree inducer (Quinlan, 1993, 2003). Decision trees have a tendency to overfit the training ...C5.0 decision tree algorithm the pruning confidence interval and the minimum ...
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Comparison of the Decision Tree Models to Intelligent Diagnosis of Liver Disease
... The performance of human skeleton during motion activities was evaluated by several types of quantitative metrics including amplitude, velocity and position of marked ...
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Bayesian averaging over Decision Tree models for trauma severity scoring
... both models have provided the same prediction accuracy, using the variable age that makes the greatest ...BN models from patient questionnaires and interviews containing contradictory ...predictive ...
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Comparison of hospital charge prediction models for gastric cancer patients: neural network vs decision tree models
... while decision tree of data mining technique was recommended because of its richness of classification arithmetic rules and appeal of ...the performance of ANN and decision tree ...
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Decision tree-based acoustic models for speech recognition
... The context-dependent GMM system with the stan- dard setting (1740k parameters) achieved higher perfor- mance than the proposed DTAM systems. However, the difference in the performance between the GMM and DTAM ...
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Performance Evaluation System for Decision Tree Algorithms
... base models are generated, at least logically, independently and in parallel, on the other hand boosting is a sequential procedure mainly applied to classification, where the performance of a preceding ...
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Improving the Performance of Vegetable Leaf Wetness Duration Models in Greenhouses Using Decision Tree Learning
... a decision learning tree can lead to an effective calibration of leaf wetness models, and that this preliminary calibration is needed when applying empirical leaf wetness models in new ...
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Students Performance Prediction Using Decision Tree Technique
... student’s performance instead of instructors’ ...instructors’ performance is the course evaluation questionnaire to evaluate based on students’ ...–decision tree algorithms, support vector ...
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Student’s Performance Analysis using Decision Tree Algorithms
... The study main objective is to find out if it is possible to predict the class (output) variable using the explanatory (input) variables which are retained in the model. Several different algorithms are applied for ...
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Predicting and Analysis of Student Performance Using Decision Tree Technique
... student’s performance instead of instructors’ ...instructors’ performance is the course evaluation questionnaire to evaluate based on students’ ...–decision tree algorithms, support vector ...
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Ensemble Models Using Logical Bayesian Decision Tree For Stream Classification And Indexing Data
... 1 S.Mohanapriya, 2 Dr.M.Rathamani 1 Research Scholar, Department of Computer Science, NGM College, Pollachi, India 2 Assistant Professor, PG Department of Computer Application, NGM College, Pollachi, India ABSTRACT: Data ...
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Moocs Video Mining Using Decision Tree J48 and Naive Bayesian Classification Models
... significant performance improvement over the original text classifiers, and over the classifiers trained from using video content based ...The performance has reached a satisfactory level for practical ...
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Decision tree and random forest models for outcome prediction in antibody incompatible kidney transplantation
... in performance of ML models is not unique to the study by Lofaro et ...the models of the same design is characterisic of small-data applications of ML algorithms which have embedded degrees of ...
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Statistical Decision Tree Models for Parsing
... In this paper, I de- scribe SPATTER, a statistical parser based on decision-tree learning techniques which constructs a complete parse for every sen- tence and achie[r] ...
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An Analysis of Decision Tree Models for Diabetes
... generate decision tree models for classification using LAD tree, NB tree and a Genetic J48 ...The decision tree based classifier models study includes various ...
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Selecting a representative decision tree from an ensemble of decision-tree models for fast big data classification
... a tree, each node is labeled by the name of the corre- sponding tested attribute, is more compact than the visual and the textual decision tree ...the tree structure or to perform additional ...
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The Tree to Success: Using Decision Tree Analysis to Predict Employee Performance and Health
... decision tree analysis provide benefits to the practice of personnel decision-making.. RQ 2 : When modeling key organizational outcomes (i.e., employee performance and.[r] ...
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Improving visual speech synthesis using Decision Tree Models
... the decision tree from having excessively long or thin ...the decision tree splits by grouping attributes which are more visually ...the decision tree’s algorithm is shown in Figure ...
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