AND/OR decision tree
A comparison of artificial neural network and decision tree for profitability in technology sector
... of decision making, if reduction of dimension is not needed or wanted, artificial neural networks may be ...wanted, decision tree analysis would be more ...When decision maker wants to give ...
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Effective Decision Tree Learning
... effective decision tree (EDT) construction algorithm that uses a new error adjusting technique (NEAT) in constructing more accurate decision tree ...in decision tree ...
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Presentation of customer foreclosure model of e-banking services using decision tree and data mining method
... of decision tree algorithms, these algorithms with acceptable accuracy (above 80%) can predict customer ...R Tree decision tree algorithm, better than other algorithms, can turn ...
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Cancer Identification VIA Weighted Entropy Method and Decision Tree Method
... the decision tree algorithm checks whether all the tuples possess same class label, then all the tuples will be grouped into one leaf ...the decision parameter x, then, ...
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Simple And Ensemble Decision Tree Classifier Based Detection Of Breast Cancer
... various decision tree algorithms including CART, ...of decision trees.Al- Sahily[2] et al in their study used different decision tree algorithms J48, Function Tree, Random Forest ...
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Uncertain Data Mining using Decision Tree and Bagging Technique
... modeling. Decision tree can handle both categorical and numerical ...A decision tree is built by using a subset from instances of dataset and remaining subset test the accuracy of constructed ...
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II. DECISION TREE CLASSIFICATION
... In the current study we introduce a new self-determined approach which has not only a suitable accuracy, but also a small-size tree which is constructed in a short time, using a small amount of memory. In this ...
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An Insight into “Decision Tree Analysis”
... bad decision can ruin whole planning and preparation that have been made in realizing the ...why decision making is termed as a tedious ...“Decision Tree Analysis”. A decision ...
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The Adaptability of Decision Tree Method in Mining Industry Safety Data
... how decision tree algorithm fits into mining ...of Decision Tree mining tool on a real-world safety records perfectly reveals useful information that are subsumed in the volume and nature of ...
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Assessing the influence of decision tree forest parameters on prediction of monthly river discharge
... of Decision Tree Forest (DTF) ( Maximum Trees in Decision Tree Forest (MTDTF) , Minimum Size Node to Split (MSNS) , and Maximum tree levels (MTL)), and assessing of their effect on ...
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Advanced Probabilistic Binary Decision Tree Using SVM for large class problem
... For the readers’ convenience, introduce the SVM briefly in section II. A brief introduction about the several widely used multiclass methods to divide the k classes in to binary class is in section III. The structure of ...
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Bezier curve and decision tree modelling for facial expression analysis
... Data ACQUISITION: We mainly used 3 datasets for training; C-K, JAFEE and PAKFEE. Readers can observe emotion samples in Fig The description of selected images for experimentation is as follows: There are about 2000 ...
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Decision Tree Algorithms for Diagnosis of Cardiac Disease Treatment
... Regression tree examination It is done when a genuine number can be taken as the anticipated result illustration (The cost of a working) To allude both of these strategies the term order and relapse tree ...
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Generating Optimized Decision Tree Based on Discrete Wavelet Transform Kiran Kumar Reddi* 1Ali Mirza Mahmood2 K.Mrithyumjaya Rao 3
... the decision making operations through mass data mining ...optimization decision tree is now an active research ...optimized decision tree with multi-attribute data source is considered ...
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HDM: A Hybrid Data Mining Technique for Stock Exchange Prediction
... In all experiments presented here, classification errors are estimated using 5-fold stratified cross validation. Cross validation is repeated ten times using different random generator seeds resulting in ten different ...
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An adaptivity hierarchy theorem for property testing
... on decision tree complexity to the setting of property testing, relying on error-correcting codes with local ...(linear) decision tree model, which is an elementary computation model that is ...
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Probabilistic Human Computer Trust Handling
... The augmentation of the dialog is done using two different kinds of dialog models. On the one hand we are using a classic dialog model based on a finite-state machine approach for the task-oriented part of the dialog. On ...
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Title: DATA MINING TO ELICIT PREDOMINANT FACTORS CAUSING INFERTILITY IN WOMEN
... different decision tree induction methods and a comparative study of the methods is also ...through decision tree induction and this is used to build a software model for the ...
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AN EMPIRICAL EVALUATION FOR THE INTRUSION DETECTION FEATURES BASED ON MACHINE LEARNING AND FEATURE SELECTION METHODS
... Suggested method is improved for test the breast cancer from mammograms. This technique achieves this testing in multiple stages. The preprocessing stage on image is done to improve image accuracy. Then features ...
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Prediction of Dumping a Product in Textile Industry
... decision tree literature. Neuro-FDT incorporates the merits of neural learning algorithms into the feedback cycle of hierarchical FDT. The method significantly improves the classification accuracy of FDT ...
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