A New Approach to Classification by Means of Jumping Emerging Patterns
نویسندگان
چکیده
Classification is one of the important fields in data analysis. Concept-based (JSM) hypotheses are a well-known approach to this task. Although the accuracy of this approach is quite good, the coverage is often insufficient. In this paper a new classification approach is presented. The approach is based on the similarity of an object to be classified to the current set of hypotheses: it attributes the new object to the class that minimizes the set of new hypotheses when a new object is added to the training set. The proposed approach provides a better coverage in compare with the classical approach.
منابع مشابه
Jumping Emerging Substrings in Image Classification
We propose a new image classi cation scheme based on the idea of mining jumping emerging substrings between classes of images represented by visual features. Jumping emerging substrings (JES) are string patterns, which occur frequently in one set of string data and are absent in another. By representing images in symbolic manner, according to their color and texture characteristics, we enable m...
متن کاملA Novel Fault Detection and Classification Approach in Transmission Lines Based on Statistical Patterns
Symmetrical nature of mean of electrical signals during normal operating conditions is used in the fault detection task for dependable, robust, and simple fault detector implementation is presented in this work. Every fourth cycle of the instantaneous current signal, the mean is computed and carried into the next cycle to discover nonlinearities in the signal. A fault detection task is complete...
متن کاملProposing a Novel Cost Sensitive Imbalanced Classification Method based on Hybrid of New Fuzzy Cost Assigning Approaches, Fuzzy Clustering and Evolutionary Algorithms
In this paper, a new hybrid methodology is introduced to design a cost-sensitive fuzzy rule-based classification system. A novel cost metric is proposed based on the combination of three different concepts: Entropy, Gini index and DKM criterion. In order to calculate the effective cost of patterns, a hybrid of fuzzy c-means clustering and particle swarm optimization algorithm is utilized. This ...
متن کاملProposing an approach to calculate headway intervals to improve bus fleet scheduling using a data mining algorithm
The growth of AVL (Automatic Vehicle Location) systems leads to huge amount of data about different parts of bus fleet (buses, stations, passenger, etc.) which is very useful to improve bus fleet efficiency. In addition, by processing fleet and passengers’ historical data it is possible to detect passenger’s behavioral patterns in different parts of the day and to use it in order to improve fle...
متن کاملHigh Fuzzy Utility Based Frequent Patterns Mining Approach for Mobile Web Services Sequences
Nowadays high fuzzy utility based pattern mining is an emerging topic in data mining. It refers to discover all patterns having a high utility meeting a user-specified minimum high utility threshold. It comprises extracting patterns which are highly accessed in mobile web service sequences. Different from the traditional fuzzy approach, high fuzzy utility mining considers not only counts of mob...
متن کامل