Principles of Data Mining

Bramer, Max

doi:10.1007/978-1-4471-7307-6

Cited by 107 publications

(68 citation statements)

References 0 publications

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“…These words clearly have the same linguistic root. Putting them together as if they were occurrences of a single word would probably give a strong indication of the content of the document whereas each word individually might not [7]. Finally, all documents in the collection are mapped to a matrix called the term.…”

Section: Stop Words and Stemmingmentioning

confidence: 99%

“…The following part moves on to describe the methods used in different aspects of TC. The Naive Bayes (NB) model has been one of the more popular methods used in TC due to its simplicity and relative effectiveness [7,27,30]. However, the performance of the NB model has turned out to be inferior to other models such as Support Vector Machine (SVM) [19], k-Near Neighbor (KNN) [43], Neural Network (NN ) [44].…”

Section: Introductionmentioning

confidence: 99%

“…Association Rule Mining (ARM) is to examine the contents of the database and find rules [7]. Another significant aspect of this study, the surveys of biomedical text mining [50,49], journal [8], and book [3] indicate that general purpose text and data mining tools are not well-suited for the biomedical domain.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Hybrid Approach of Association Rule & Hidden Makov Model to Improve Efficiency Medical Text Classification

Al-qozani¹,

AL-Wagih²

2018

IJCATR

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Abstract:Text classification problem is a set of documents be classified into a predefined set of categories, each document is classified based on a set of features (words). However, some of the words not relevant to a category which causes a gap between words relevance in a document. A lot of research articles in public databases, and The digitization of critical medical information such as lab reports, patients records, research papers, and anatomic images tremendous amounts of biomedical research data are generated every day. So that, the classification this data and retrieving information relevant to information users' needs have been a primary research issue in the field of Information Retrieval, and the adoption of classification has been applied to tackle this particular problem. In this paper, we propose a hybrid model for the classification of biomedical texts according to their content, using Association Rules and Hidden Markov Model as classifier. In order to demonstrate it, we present a set of experiments performed on OHSUMED biomedical text corpora. Our classifier compared with Naive Bayes and Support Vector Machine models. The evaluation result shows that the proposed classification is complete and accurate when compared with Naive Bayes and Support Vector Machine models.

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Section: Stop Words and Stemmingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Hybrid Approach of Association Rule & Hidden Makov Model to Improve Efficiency Medical Text Classification

Al-qozani¹,

AL-Wagih²

2018

IJCATR

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“…But it has a drawback, when large values bear down the smaller ones. Continuous attributes must be normalized in order to take over this major problem so that they have same influence on the distance measure between distances [22].…”

Section: K-nearest Neighbor (K-nn)mentioning

confidence: 99%

Data Mining for diagnosis in Healthcare Sector-a review

2017

IJASRE

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“…[3]. "Neural networks are powerful mathematical models suitable for almost all data mining tasks, with special emphasis on classification and estimation problems" [9].…”

Section: Identification Of Neural Networkmentioning

confidence: 99%

A Comparative Study of Various Data Mining Techniques: Statistics, Decision Trees and Neural Networks

Balar¹,

Naji²

2016

IJCATR

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Abstract:In this paper we focus on some techniques for solving data mining tasks such as: Statistics, Decision Trees and Neural Networks. The new approach has succeed in defining some new criteria for the evaluation process, and it has obtained valuable results based on what the technique is, the environment of using each techniques, the advantages and disadvantages of each technique, the consequences of choosing any of these techniques to extract hidden predictive information from large databases, and the methods of implementation of each technique. Finally, the paper has presented some valuable recommendations in this field.

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Principles of Data Mining

Cited by 107 publications

References 0 publications

A Hybrid Approach of Association Rule & Hidden Makov Model to Improve Efficiency Medical Text Classification

A Hybrid Approach of Association Rule & Hidden Makov Model to Improve Efficiency Medical Text Classification

Data Mining for diagnosis in Healthcare Sector-a review

A Comparative Study of Various Data Mining Techniques: Statistics, Decision Trees and Neural Networks

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