tree induction algorithms
Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data
... Decision-tree induction algorithms have been success- fully used in drug-design related applications ...these algorithms when com- pared to other machine learning techniques ...
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Integrating Information Theory Measures and a Novel Rule-Set-Reduction Tech-nique to Improve Fuzzy Decision Tree Induction Algorithms
... decision tree generated by the improved Fuzzy ID3 algorithm, we compared the performance of our method with the performance of ...Decision Tree), Random Forest and Fuzzy‐EBY [41]; Fuzzy‐ EBY generates fuzzy ...
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A survey of cost sensitive decision tree induction algorithms
... the algorithms identified in the literature with respect to the taxonomy shown in Figure 2 and shows the significant volume of work in this field in each of the ...the algorithms incorporate test costs, ...
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Efficient Algorithms for Decision Tree Cross-validation
... decision tree induction algorithms assume that all data reside in main ...a tree from a large database, this may not be realistic: data have to be loaded from disk into main memory when ...
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Inducing decision trees with an ant colony optimization algorithm
... the induction of decision trees in the context of the classification task in data ...decision tree that a particular branch—(attribute, value) pair—appears to discriminate between multiples occurrences of ...
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Performance Evaluation System for Decision Tree Algorithms
... the algorithms date back in the ...decision tree algorithms tend to automate the entire process of hypothesis generation and then validation much more completely and in a much more integrated way ...
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The Eigen Distribution of an AND-OR Tree under Directional Algorithms
... [10] Suzuki, T. and Nakamura, R.: Probability distributions achieving the equilibrium of an AND-OR tree under directional algorithms. Lecture Notes in Engineering and Computer Science: Proceedings of The ...
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B AB 5 C AC 3 D ABGED 9 E ABGE 7 F ABGEF 8 G ABG 6 A BEDA 3 C BC 1 D BCD 2 E BE 1 F BEF 2 G BG 1
... Find a minimum spanning tree for the graph in Figure 9.82 using both Prim's and Kruskal's algorithms.. Is this minimum spanning tree unique?[r] ...
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Performance Analysis of Classification Tree Learning Algorithms
... decision tree pruning. For every non-leaf sub tree of the original decision tree, the change in misclassification over the test set is ...regression tree learner that uses information variance ...
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Semi Supervised Classification in Educational Data Mining: Students’ Performance Case Study
... classification algorithms on student’s dataset and J48 was found as the best algorithm in terms of accuracy ...the algorithms CHAID and CART were applied to get two decision trees classifying succesful and ...
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Assessment of Decision Tree Algorithms on Student’s Recital
... decision tree algorithms (ID3 and ...the algorithms and concludes that ...decision tree algorithms (ID3, ...C4.5 algorithms are implemented on different types of tumor datasets ...
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XML Tree Pattern Matching Algorithms: Survey
... XML tree pattern queries. The existing holistic algorithms for XML tree pattern matching queries exhibit sub-optimality problem as they consider intermediate results before taking final ...
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Efficient Algorithms for Finding 2-Medians of a Tree
... Goldman [6] derived a linear time algorithm for finding the 1-median of a tree with arbitrary edge lengths and node weights. Using Goldman’s algorithm, Dearing, Frances, and Low [4] gave efficient ...
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Anticipating of Cardiovascular Heart Diseases using Computer based Poly Trees Model
... poly tree and Directed Acyclic Graphical model DAG to predict all the cases that can cause Cardiovascular Heart ...the tree based on the rules of creating a Poly-Tree ...poly tree model ...
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Evolutionary Algorithms in Decision Tree Induction
... Those algorithms do not claim to find the global optimum, but are able to converge rapidly towards a local ...exact algorithms (that will be called heuristics in the rest of this chapter) are certainly not ...
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Generalized weighted tree similarity algorithms for taxonomy trees
... weighted tree similarity ...proposed algorithms efficiently use the missing value in order to distinguish among taxonomy trees that have the same matching value, but, have dif- ferent missing ...
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Feature Induction and Network Mining with Clustering Tree Ensembles
... feature induction method based on random forests [5] was ...decision tree to a feature ...each tree in the forest and they were further encoded using ...
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Experimental study of performance of minimum spanning tree algorithms
... traversal and finding Several have been developed for algorithms performance based be weights that can structures used by finding goal of this and Prim's have Spanning study is to for a [r] ...
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Accelerating t-SNE using Tree-Based Algorithms
... dual-tree algorithms reduce the number of pairwise forces that needs to be computed by exploiting the fact that the forces exerted between two small groups of points are all very similar whenever these two ...
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Student’s Performance Analysis using Decision Tree Algorithms
... concerns with developing and modeling methods that discover knowledge from data originating from educational environments. This paper presents the use of data mining approach to study students’ performance in CSC207 ...
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