Naive Bayesian classi ers which make independence assumptions perform remarkably well on some data sets but poorly on others. We explore ways to improve the Bayesian classi er by searching for dependencies among attributes. We propose and evaluate two algorithms for detecting dependencies among attributes and show that the backward sequential elimination and joining algorithm provides the most ...

Web mining related exploration is getting the chance to be more essential these days in view of the reason that a lot of information is overseen through the web. Web utilization is expanding in an uncontrolled way. A particular framework is required for controlling such extensive measure of information in the web space. Web mining is ordered into three noteworthy divisions: Web content mining, ...

The use of multiple features by a classifier often leads to a reduced probability of error, but the design of an optimal Bayesian classifier for multiple features is dependent on the estimation of multidimensional joint probability density functions and therefore requires a design sample size that, in general, increases exponentially with the number of dimensions. The classification method desc...

In order to strengthen the supervision and management of environmental pollution timely understand record basic information potential enterprises institutions, this paper proposes a general survey inventory method sources based on big data technology under machine learning. Firstly, evaluates screens provided by government departments, constructs learning classification model, uses variety algo...

The“curse of dimensionality”provides a powerful impetus to explore alternative data structures and representations for text processing. This paper presents a method for preparing a dataset for classification by determining the utility of a very small number of related dimensions via a Discriminative Multinomial Naive Bayes process, then using these utility measurements to weight these dimension...

This paper mainly deals with feature extraction algorithm used to improve the predicted accuracy of the classification. This paper applies with Principal Component analysis as a feature evaluator and ranker for searching method. Naive Bayes algorithm is used as a classification algorithm. It analyzes the hepatitis patients from the UC Irvine machine learning repository. The results of the class...

This paper investigates boosting naive Bayesian classiica-tion. It rst shows that boosting cannot improve the accuracy of the naive Bayesian classiier on average in a set of natural domains. By analyzing the reasons of boosting's failures, we propose to introduce tree structures into naive Bayesian classiication to improve the performance of boosting when working with naive Bayesian classiicati...

In this paper, we propose a novel face photo retrieval system using sketch drawings. By transforming a photo image into a sketch, we reduce the difference between photo and sketch significantly, thus allow effective matching between the two. To improve the synthesis performance, we separate shape and texture information in a face photo, and conduct transformation on them respectively. Finally a...

This paper investigates boosting naive Bayesian classiica-tion. It rst shows that boosting cannot improve the accuracy of the naive Bayesian classiier on average in a set of natural domains. By analyzing the reasons of boosting's failures, we propose to introduce tree structures into naive Bayesian classiication to improve the performance of boosting when working with naive Bayesian classiicati...