147 hasil untuk machine learning

Automating XML Markup using Machine Learning Techniques

Shazia Akhtar; Ronan Reilly; John Dunnion

Journal of Systemics, Cybernetics and Informatics, Vol. 2 No. 5 · 2004 · Inggris · DOAJ

…the Self-Organising Map (SOM) algorithm in conjunction with an inductive learning algorithm, C5.0. The SOM algorithm clusters the XML marked-up documents on a two-dimensional map such that documents having similar content are placed close to each other. The C5.0 algorithm learns and applies markup…

Finding protein sites using machine learning methods

Jaime Leonardo Bobadilla Molina; Fernando Niño; Tobías Mojica

Ingeniería e Investigación, Vol. 23 No. 3 · 2003 · Inggris · DOAJ Scopus

…nonsites that lack this role. 3. A single query site. A support vector machine classifier is built using feature vectors where each component represents a property in a given volume. Validation against an independent test set shows that this recognition approach has high sensitivity and…

Application of machine learning in SNP discovery

Cregan Perry B; Choi Ik-Young; Hyten David L dkk.

BMC Bioinformatics, Vol. 7 No. 1 · 2006 · Inggris · DOAJ Scopus

…SNP predictions even with stringent parameter values. We developed a machine learning (ML) method to augment PolyBayes to improve its prediction accuracy. ML methods have also been successfully applied to other bioinformatics problems in predicting genes, promoters, transcription factor binding…

Intrusion detection method based on machine learning

TIAN Xin-guang1; GAO Li-zhi2; ZHANG Er-yang1

Tongxin xuebao, Pp 108-114 (2006) · 2006 · Tionghoa · DOAJ Scopus

A new intrusion detection method was presented based on machine learning for intrusion detection systems using shell commands as audit data.In the method,multiple dictionaries of shell command sequences of different lengths were constructed to represent the normal behavior profile of a network…

Juga tersedia di: DOAJ

Application of inductive machine learning in data mining

Vladislav Miškovic

Vojnotehnički Glasnik, Vol. 49 No. 4-5 · 2001 · Inggris · DOAJ Scopus

This paper considers the application of inductive machine learning methods in data mining and knowledge discovery in databases tasks. Some characteristics of the author's noncommercial System for Data Mining and Knowledge Discovery are presented as Well as the experimental comparison of its…

Applications of Machine Learning in Cancer Prediction and Prognosis

Joseph A. Cruz; David S. Wishart

Cancer Informatics, Vol. 2 · 2006 · Inggris · DOAJ Scopus

Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to “learn” from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly…

Juga tersedia di: DOAJ

Classification of grapevine cultivars using Kirlian camera and machine learning

Danijel SKOČAJ; Igor KONONENKO; Irma TOMAŽIČ dkk.

Acta Agriculturae Slovenica, Vol. 75 No. 1 · 2000 · Slovenia · DOAJ Scopus

…acquired coronas of the berries with numerical parameters and used machine learning algorithms to classify grapevine cultivars. We tested this method on eight grapevine cultivars, performing different tests. The results show that coronas of grapevine berries contain useful information about…

Matematičko modeliranje induktivnog mašinskog učenja / Mathematical modeling of inductive machine learning

Vladislav Miškovic

Vojnotehnički Glasnik, Vol. 51 No. 1 · 2003 · Inggris · DOAJ Scopus

U radu se razmatra modeliranje induktivnog mašinskog učenja (inductive machine learning). Izloženi su najznačajniji matematički modeli i njihov odnos prema praktično realizovanim algoritmima. Prikazane su osnovne karakteristike najpoznatijih svetskih i jednog sopstvenog sistema induktivnog učenja…

Effectiveness of active forgetting in machine learning applied to financial problems

Hirotaka Nakayama; Kengo Yoshii

Journal of Telecommunications and Information Technology, Iss 3 (2002) · 2002 · Inggris · DOAJ Scopus

…this circumstance, in particular, it has been observed that additional learning plays an effective role. However, since the rule for classification becomes more and more complex with only additional learning, some appropriate forgetting is also necessary. It seems natural that many data are…

Tandem machine learning for the identification of genes regulated by transcription factors

Schuetz Erin G; Mehta Saumil; Raheja Venetia dkk.

BMC Bioinformatics, Vol. 6 No. 1 · 2005 · Inggris · DOAJ Scopus

…sites recognized by the factor. In this study, we have developed a tandem machine learning approach for the identification of regulatory target genes based on these parameters and on the corresponding binding site information contents that measure the affinities of the factor for these cognate…

Homology Induction: the use of machine learning to improve sequence similarity searches

King Ross D; Karwath Andreas

BMC Bioinformatics, Vol. 3 No. 1 · 2002 · Inggris · DOAJ Scopus

…Homology Induction (HI), a new approach to inferring homology. HI uses machine learning to bootstrap from standard sequence similarity search methods. First a standard method is run, then HI learns rules which are true for sequences of high similarity to the target (assumed homologues) and not true…

Using Abductive Machine Learning for Online Vibration Monitoring of Turbo Molecular Pumps

R.E. Abdel-Aal; M. Raashid

Shock and Vibration, Vol. 6 No. 5-6 · 1999 · Inggris · DOAJ Scopus

…online monitoring scheme. This paper describes the use of modern machine learning techniques for online monitoring of the pump condition through the measurement and analysis of pump vibrations. Abductive machine learning is used for modeling the pump status as ‘good’ or ‘bad’ using both radial and…

Machine learning techniques in disease forecasting: a case study on rice blast prediction

Kapoor Amar S; Kaundal Rakesh; Raghava Gajendra PS

BMC Bioinformatics, Vol. 7 No. 1 · 2006 · Inggris · DOAJ Scopus

…which further increased to r = 0.77 and %MAE = 36.66 when support vector machine (SVM) based method was used. Similarly, cross-location validation achieved r = 0.48, 0.56 and 0.66 using REG, BPNN and GRNN respectively, with their corresponding %MAE as 77.54, 66.11 and 58.26. The SVM-based method…

A scalable machine-learning approach to recognize chemical names within large text databases

Wren Jonathan D

BMC Bioinformatics, Vol. 7 No. Suppl 2 · 2006 · Inggris · DOAJ Scopus

Abstract Motivation The use or study of chemical compounds permeates almost every scientific field and in each of them, the amount of textual information is growing rapidly. There is a need to accurately identify chemical names within text for a number of informatics efforts such as database…

Review of "Data Mining: Practical Machine Learning Tools and Techniques" by Witten and Frank

Azuaje Francisco

BioMedical Engineering OnLine, Vol. 5 No. 1 · 2006 · Inggris · DOAJ Scopus

Building a protein name dictionary from full text: a machine learning term extraction approach

Campagne Fabien; Shi Lei

BMC Bioinformatics, Vol. 6 No. 1 · 2005 · Inggris · DOAJ Scopus

Abstract Background The majority of information in the biological literature resides in full text articles, instead of abstracts. Yet, abstracts remain the focus of many publicly available literature data mining tools. Most literature mining tools rely on pre-existing lexicons of biological names…

A machine learning strategy to identify candidate binding sites in human protein-coding sequence

Leong Bernard; Down Thomas; Hubbard Tim JP

BMC Bioinformatics, Vol. 7 No. 1 · 2006 · Inggris · DOAJ Scopus

Abstract Background The splicing of RNA transcripts is thought to be partly promoted and regulated by sequences embedded within exons. Known sequences include binding sites for SR proteins, which are thought to mediate interactions between splicing factors bound to the 5' and 3' splice sites. It…

Machine learning and word sense disambiguation in the biomedical domain: design and evaluation issues

Liu Hongfang; Dimova Rositsa; Markatou Marianthi dkk.

BMC Bioinformatics, Vol. 7 No. 1 · 2006 · Inggris · DOAJ Scopus

…situations, but the problem is still a challenging one. Supervised WSD machine learning (ML) methods have been applied in the biomedical domain and have shown promising results, but the results typically incorporate a number of confounding factors, and it is problematic to truly understand the…