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85 results for “Applied Machine Learning”
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Research ArticleOpen accessIn the abstractA Hybrid Approach to Pronominal Anaphora Resolution in ArabicAbdullatif Abolohom, Nazlia OmarOne of the challenges in natural language processing is to determine which pronouns to be referred to their intended referents in the discourse. Performing anaphora resolution is considered as an important task for a number of natural language processing applications such as information extraction, question answering and text summarization. Most of the earlier works of anaphora resolution have been applied … …Journal of Computer Science, Vol. 11, Issue 5 · 17 Aug 2015 · 7,098 accessesView PDFCite
Research ArticleOpen accessIn the abstractStatistical Analysis and Learning Method on Users' FeedbacksDoris Hooi-Ten Wong, Sureswaran RamadassProblem statement: The purpose of this study was constructing an effective algorithm in order to learn the users’ feedbacks from their displayed visualization. This is due to existing visualization tools typically involve presenting network data regardless of considering level of network data knowledge among different levels of computer users. The machine learning algorithm has been applied in order to find … …Journal of Computer Science, Vol. 7, Issue 9 · 26 Jul 2011 · 6,531 accessesView PDFCite
Research ArticleOpen accessIn the abstractFeature Selection for High Dimensional Data: An Evolutionary Filter ApproachAnwar Ali Yahya, Addin Osman, Abd Rahman Ramli, Adlan BalolaProblem statement: Feature selection is a task of crucial importance for the application of machine learning in various domains. In addition, the recent increase of data dimensionality poses a severe challenge to many existing feature selection approaches with respect to efficiency and effectiveness. As an example, genetic algorithm is an effective search algorithm that lends itself directly to feature selection; … …Journal of Computer Science, Vol. 7, Issue 5 · 9 May 2011 · 7,949 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproving the Performance of Machine Learning Based Multi Attribute Face Recognition Algorithm Using Wavelet Based Image Decomposition TechniqueS. Sakthivel, M. RajaramProblem statement: Recognizing a face based attributes is an easy task for a human to perform; it is closely automated and requires little mental effort. A computer, on the other hand, has no innate ability to recognize a face or a facial feature and must be programmed with an algorithm to do so. Generally, to recognize a face, different kinds … …Journal of Computer Science, Vol. 7, Issue 3 · 7 Mar 2011 · 6,911 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Evaluation of Phone Duration Models for Greek Emotional SpeechAlexandros Lazaridis, Vasiliki Bourna, Nikos FakotakisProblem statement: In this study we cope with the task of phone duration modeling for Greek emotional speech synthesis. Approach: Various well established machine learning techniques are applied for this purpose to an emotional speech database consisting of five archetypal emotions. The constructed phone duration prediction models are built on phonetic, morphosyntactic and prosodic features that can be extracted only … …Journal of Computer Science, Vol. 6, Issue 3 · 31 Mar 2010 · 7,066 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimizing Feature Construction Process for Dynamic Aggregation of Relational AttributesRayner AlfredProblem statement: The importance of input representation has been recognized already in machine learning. Feature construction is one of the methods used to generate relevant features for learning data. This study addressed the question whether or not the descriptive accuracy of the DARA algorithm benefits from the feature construction process. In other words, this paper discusses the application of genetic … …Journal of Computer Science, Vol. 5, Issue 11 · 30 Nov 2009 · 6,935 accessesView PDFCite
Research ArticleOpen accessIn the abstractLandslide Susceptibility Analysis Using Numerical and Neural Network, Near Kedarnath, Uttarakhand, IndiaVinay Kumar Singh, Tariq Anwar Ansari, Vikram Vishal, T.N. SinghThe major concern in hilly regions is the stability of those slopes, which have been proclaimed due to unplanned excavation and uneven blasting during road widening and development activity. These slopes again become more vulnerable under dynamic loading and/or various types of human involvement, heavy rainfall and seismic activity. Failure of these slopes leads to loss of property and human … …American Journal of Environmental Sciences, Vol. 16, Issue 1 · 9 Mar 2020 · 7,778 accessesView PDFCite
Research ArticleOpen accessIn the abstractMissing Values Treatment and Feature Reduction Analysis to Enhance ClassificationD. Muralidharan, K. Renuka, Mulagala Jaswant et al.Datasets may have large number of features which makes it hard and time consuming to classify. Additionally, they may have irrelevant and noise features too with missing values. The missing values should be treated in a proper way so that the classifier accuracy can be improved. There is also a need to reduce features and select only the features necessary … …Journal of Computer Science, Vol. 16, Issue 2 · 20 Feb 2020 · 8,119 accessesView PDFCite
Research ArticleOpen accessIn the abstractA New Cooperative Algorithm Based on PSO and K-Means for Data ClusteringMehdi Neshat, Shima Farshchian Yazdi, Daneyal Yazdani, Mehdi SargolzaeiProblem statement: Data clustering has been applied in multiple fields such as machine learning, data mining, wireless sensor networks and pattern recognition. One of the most famous clustering approaches is K-means which effectively has been used in many clustering problems, but this algorithm has some drawbacks such as local optimal convergence and sensitivity to initial points. Approach: Particle Swarm Optimization … …Journal of Computer Science, Vol. 8, Issue 2 · 19 Nov 2011 · 7,975 accessesView PDFCite
Research ArticleOpen accessIn the abstractSentiment Analysis: Comparative Study between GSVM and KNNHany Mohamed, Ayman Atia, Mostafa-Sami M. MostafaSentiment classification aims detecting general opinion of users in social media towards business products or daily life events. The classification tells whether sentiment is positive or negative. Techniques of sentiment classification are categorized into lexical analysis and machine learning techniques. In this paper, we propose a comparative study between SVM applied genetics (GSVM) against KNN algorithm in terms of speed … …American Journal of Applied Sciences, Vol. 15, Issue 6 · 1 Aug 2018 · 8,363 accessesView PDFCite