Search Results - (( java implementation mining algorithm ) OR ( using spatial learning algorithm ))

Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

“…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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Mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

“…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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A web-based implementation of k-means algorithms by Lee, Quan

“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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GIS-based air quality modelling: spatial prediction of PM10 for Selangor State, Malaysia using machine learning algorithms by Tella, A., Balogun, A.-L.

“…Although some studies have predicted air pollutants such as particulate matter (PM) using machine learning algorithms (MLAs), there is a paucity of studies on spatial hazard assessment with respect to the air quality index (AQI). …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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A review of the inter-correlation of climate change, air pollution and urban sustainability using novel machine learning algorithms and spatial information science by Balogun, A.-L., Tella, A., Baloo, L., Adebisi, N.

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A cognitive mapping approach in real-time haptic rendering interaction for improved spatial learning ability among autistic people / Kesavan Krishnan by Kesavan , Krishnan

“…Nevertheless, the use of haptic technology in terms of spatial learning is still not fully utilized, and this weakens autistic people in the process of learning about their surroundings. …”
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Building detection using object-based Image analysis (OBIA) and machine learning (ML) algorithms / Hanani Mohd Shahar by Mohd Shahar, Hanani

“…Thus, by enhancing the classification techniques in OBIA, building extraction accuracy using ML algorithms for medium resolution images can be improved and the expenses also can be reduced indirectly.…”
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Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments by Gadipudi, N., Elamvazuthi, I., Lu, C.-K., Paramasivam, S., Su, S.

“…On the other hand, learning-based methods automatically learn the features required through motion mapping. …”
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Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments by Gadipudi, N., Elamvazuthi, I., Lu, C.-K., Paramasivam, S., Su, S.

“…On the other hand, learning-based methods automatically learn the features required through motion mapping. …”
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Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification by Prathama, Y.B.H., Shapiai, M.I., Aris, S.A.M., Ibrahim, Z., Jaafar, J., Fauzi, H.

“…Instead of selecting features, the proposed algorithm employs a feature scaling system to scale the importance of each band by using Genetic Algorithm (GA) altogether with Extreme Learning Machine (ELM) as classifier, with 1 signifying the most important bands, declining until 0 for the unused bands, as opposed to the 1 and 0 selection system used in BPSO-CSP. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

“…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield. by Md. Sap, Mohd. Noor, Awan, A. Majid

“…In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering climate data. …”
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Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis by Kabir Ahmad, Farzana, Kamaruddin, Siti Sakira, Yusof, Yuhanis, Yusoff, Nooraini

“…Complex event pattern detection has become an emerging research area in various monitoring applications. For learning and predicting the event patterns, dynamic Bayesian network (DBN) with Hidden Markov Model (HMM) and heuristic search learning algorithms have been a popular technique used in which structure learning is trained to classify complex events pattern. …”
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Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids by Chiaverini, Luca, Macdonald, David W., Hearn, Andrew J., Kaszta, Zaneta, Ash, Eric, Bothwell, Helen M., Can, Ozgun Emre, Channa, Phan, Clements, Gopalasamy Reuben *, Haidir, Iding Achmad, Kyaw, Pyae Phyoe, Moore, Jonathan H., Rasphone, Akchousanh, Tan, Cedric Kai Wei, Cushman, Samuel A.

“…The latter is a machine learning non-parametric algorithm, more tolerant than other approaches in its assumptions, which has often been shown to outperform parametric algorithms. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

“…Using BBNs, different learning strategies were explored and compared with k-fold using negative entropy loss. …”
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Brain tumor image segmentation using deep learning approach by Darshan, Suresh

“…Deep learning algorithm is able to provide good tumor segmentation results compared to other conventional segmentation algorithms as it learns from the labeled brain MRIs to predict the location of tumor region and consequently segment the tumor. …”
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