Groundwater potential mapping is an important prerequisite for evaluating the exploitation, utilization, and recharge of groundwater. The study uses BFT (best-first decision tree classifier), CART (classification regression tree), FT (functional trees), EBF (evidential belief function) benchmark models, RF-BFTree, RF-CART, RF-FT ensemble models to map groundwater Wuqi County, China. Firstly, se...

We investigate several algorithms related to the parsing problem for weighted automata, under the assumption that the input is a string rather than a tree. This assumption is motivated by several natural language processing applications. We provide algorithms for the computation of parse-forests, best tree probability, inside probability (called partition function), and prefix probability. Our ...

Two segmentation methods based on the minimum spanning tree principle are evaluated with respect to each other. The hierarchical minimum spanning tree method is also evaluated with respect to human segmentations. Discrepancy measure is used as best suited to compute the segmentation error between the methods. The evaluation is done using gray value images. It is shown that the segmentation resu...

Discovery of sequential patterns is becoming increasingly useful and essential in many scientific and commercial domains. Enormous sizes of available datasets and possibly large number of mined patterns demand efficient, scalable, and parallel algorithms. Even though a number of algorithms have been developed to efficiently parallelize frequent pattern discovery algorithms that are based on the...

One of the main goals in Knowledge Discovery is to find interesting associations between values of attributes, those that are meaningful in a domain of interest. The most effective way to reduce the amount of discovered patterns is to apply two interestingness measures, subjective and objective. Subjective measures are based on the subjectivity and understandability of users examining the patte...

The paper investigates the acceleration of t-SNE—an embedding technique that is commonly used for the visualization of high-dimensional data in scatter plots—using two treebased algorithms. In particular, the paper develops variants of the Barnes-Hut algorithm and of the dual-tree algorithm that approximate the gradient used for learning t-SNE embeddings in O(N logN). Our experiments show that ...