Reliable Data Selection using Similarity Measure

Improving Imbalanced data classification accuracy by using Fuzzy Similarity Measure and subtractive clustering

 Classification is an one of the important parts of data mining and knowledge discovery. In most cases, the data that is utilized to used to training the clusters is not well distributed. This inappropriate distribution occurs when one class has a large number of samples but while the number of other class samples is naturally inherently low. In general, the methods of solving this kind of prob...

Ranking of generalized fuzzy numbers using distance measure and similarity measure

Data Compression Using a Sort-Based Context Similarity Measure

Every symbol in the data can be predicted by taking the immediately preceding symbols, or context, into account. This paper proposes a new adaptive data-compression method based on a context similarity measure. We measure the similarity of contexts using a context sorting mechanism. The aim of context sorting is to store a set of contexts in a speci"c order so that contexts more similar to the ...

Reliable bands guided similarity measure for noise-robust speech recognition

Under noisy conditions, due to the redundancy of speech signal, there are some spectral bands (Reliable Bands) whose local SNR’s are high enough to be used effectively by a recognizer. A novel, phonetically motivated Reliable Bands Guided similarity measure (RBG measure) is proposed in this study. It has the following features. Firstly, for reference spectrum, frequency bands which have larger ...

Validation of Deduplication in Data using Similarity Measure

Deduplication is the process of determining all categories of information within a data set that signify the same real life / world entity. The data gathered from various resources may have data high quality issues in it. The concept to identify duplicates by using windowing and blocking strategy. The objective is to achieve better precision, good efficiency and also to reduce the false positiv...