Reuniões sem fim

Minimização do Impacto do Problema de Desvio de Conceito por Meio de Acoplamento em Ambiente de Aprendizado Sem Fim

Machine Learning (ML) is a research subarea of Artificial Intelligence that aims to develop computer programs that can evolve with new experiences. Among the many ML goals, the endless learning, i.e., methods that would enable computer systems to autonomously improve their own performance, based on previously learnt information, is of particular interest in the research described in this paper....

The UK FIM+FAM: development and evaluation

Surprising Results of Trie-based FIM Algorithms

Trie is a popular data structure in frequent itemset mining (FIM) algorithms. It is memory-efficient, and allows fast construction and information retrieval. Many trie-related techniques can be applied in FIM algorithms to improve efficiency. In this paper we propose new techniques for fast management, but more importantly we scrutinize the well-known ones especially those which can be employed...

Validation of FIM-MDS crosswalk conversion algorithm.

In this study, we performed a validation analysis of a crosswalk that converts Functional Independence Measure (FIM) scores to Minimum Data Set (MDS) scores and vice versa in order to achieve score compatibility. Data from 2,130 patients were obtained from the Department of Veteran Affairs' Austin Automation Center. The conversion algorithm was tested at the (1) individual patient level, (2) cl...

Parallel FIM Approach on GPU using OpenCL

In this paper, we describe GPU-Eclat algorithm, a GPU (General Purpose Graphics Processing Unit) enhanced implementation of Frequent Item set Mining (FIM). The frequent itemsets are extracted from a transactional database as it is a essential assignment in data mining field because of its broad applications in mining association rules, time series, correlations etc. The Eclat approach is the ty...