Decision tree model

About: Decision tree model is a research topic. Over the lifetime, 2256 publications have been published within this topic receiving 38142 citations.

Constructing phylogenetic tree using svds of flattenings

Abstract: Phylogenetic algebraic geometry is concerned with certain complex projective algebraic varieties derived from finite trees. This paper gives a self-contained introduction to this subject and introduces a new, statistically consistent algorithm for phylogenetic tree construction that uses the singular value decompositions of flattenings of statistical models. We use rank condition of flattenings determining a partition of phylogenetic tree to be a split. Starting with an mutiple sequence alignment of n DNA sequences, we show that SVD gives us to decide whether a split of the taxa occurs in their phylogenetic tree, assuming only that evolution follows a tree model. Using this fact, we have developed an algorithm to construct a phylogenetic tree by computing only O(n²) SVDs relating to the hierarchy of flattenings. Furthermore we have obtained more efficient algorithm comparing to the previous one which Eriksson has got. Also we could save computing time for SVDs of flattenings.

Building Data Mining Decision Tree Model for Predicting Employee Performance

Abstract: Human resource is one of the functions of a company that is considered as an asset. Therefo re, the theory of performance qualificat ion was adopted by the company in order to get an overview of employee performance. Furthermore, the company needs an effective method to predict the performance not only for the employees but also for the new applic ants. The goals of this research are to get a decision tree model of the employee performance. By learning employee data, the performance of the new applicants could be predicted. The study would provide the characteristic of new applicants who will give better performance than other applicants . The data from a company in Indonesia will have been used for this research. The data mining technique will be applied to the data of operators (such as admins, clerks, cashiers, machine operators, and security offi cers). The data mining technique was use d is decision tree. The decision tree technique was commonly used for a supervised learning data. The decision tree technique also has advantages compared others, because of its ability to produce information that is easy to understand. The result of this research shown the high dependency of employee performance with employment type (work contract). It also means that employees are encouraged to provide good performance to the company if those employees have become p ermanent employees. This research also showed that there is no relationship between employee performances with gender or position grade.

Computational Complexity of Iterated Maps on the Interval (Extended Abstract)

Abstract: The exact computation of orbits of discrete dynamical systems on the interval is considered. Therefore, a multiple-precision floating point approach based on error analysis is chosen and a general algorithm is presented. The correctness of the algorithm is shown and the computational complexity is analyzed. As a main result, the computational complexity measure considered here is related to the Ljapunow exponent of the dynamical system under consideration.