Milos Jovanovic

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Clustering algorithms are well-established and widely used for solving data-mining tasks. Every clustering algorithm is composed of several solutions for specific sub-problems in the clustering process. These solutions are linked together in a clustering algorithm, and they define the process and the structure of the algorithm. Frequently, many of these(More)
— Typical data mining algorithms follow a so called " black-box " paradigm, where the logic is hidden from the user not to overburden him. We show that " white-box " algorithms constructed with reusable components design can have significant benefits for researchers, and end users as well. We developed a component-based algorithm design platform, and used(More)
We propose a generic decision tree framework that supports reusable components design. The proposed generic decision tree framework consists of several sub-problems which were recognized by analyzing well-known decision tree induc-CTREE. We identified reusable components in these algorithms as well as in several of their partial improvements that can be(More)
—Several external indices that use information not present in the dataset were shown to be useful for evaluation of representative based clustering algorithms. However, such supervised measures are not directly useful for construction of better clustering algorithms when class labels are not provided. We propose a method for identifying internal cluster(More)
Conditional probabilistic graphical models provide a powerful framework for structured regression in spatio-temporal datasets with complex correlation patterns. However, in real-life applications a large fraction of observations is often missing, which can severely limit the representational power of these models. In this paper we propose a Marginalized(More)
This paper presents a contribution to the study of control law structures and to the selection of relevant sensory information for humanoid robots in situations where dynamic balance is jeopardized. In the example considered, the system first experiences a large disturbance, and then by an appropriate control action resumes a " normal " posture of standing(More)
This paper proposes a framework for automated design of component-based decision tree algorithms. These algorithms are being constructed by interchanging components extracted from decision tree algorithms and their partial improvements. Manual selection of the best-suited algorithm for a specific problem is a complex task because of the huge algorithmic(More)
—University students are usually taught data mining through black-box data mining algorithms, which hide the al-gorithm's details from the user and optionally allow parameter adjustment. This minimizes the effort required to use these algorithms. On the other hand, white-box algorithms reveal the algorithm's structure, allowing users to assemble algorithms(More)