Classification using naive bayes algorithm for air quality dataset has an accuracy rate of 39.97%. This result is considered not good and by all existing data attributes. By doing pre-processing, namely feature selection the gain ratio algorithm, Naive Bayes increases to 61.76%. proves that can improve performance classification. dataset. While Water Quality 93.18%. These results are 95.73%. Ba...

Traditional text classification methods utilize term frequency (tf) and inverse document frequency (idf) as the main method for information retrieval. Term weighting has been applied to achieve high performance in text classification. Although TFIDF is a popular method, it is not using class information. This paper provides an improved approach for supervised weighting in the TFIDF model. The t...

We describe a simple method for certifying that an experimental device prepares a desired quantum state ρ. Our method is applicable to any pure state ρ, and it provides an estimate of the fidelity between ρ and the actual (arbitrary) state in the lab, up to a constant additive error. The method requires measuring only a constant number of Pauli expectation values, selected at random according t...

The context-tree weighting method (Willems, Shtarkov, and Tjalkens [1995]) is a sequential universal source coding method that achieves the Rissanen lower bound [1984] for tree sources. The same authors also proposed context-tree maximizing, a two-pass version of the context-tree weighting method [1993]. Later Willems and Tjalkens [1998] described a method based on ratios (betas) of sequence pr...

Various approaches to index term-weighting have been investigated. In fact, term-weighting is an indispensable process for document ranking in most retrieval systems. As well actual information retrieval systems have to deal with explosive growth of documents of various sizes and terms of various frequencies because an appropriate term-weighting scheme has a crucial impact on the overall perfor...