In the recent years machine learning algorithms have developed further and various applications are taking advantage of this advancement. Modern is now used in district heating for more precise realistic heat demand prediction. Machine methods like Artificial Neural Network (ANN), Linear Regression (LR), Decision Tree (DT) commonly adopted prediction to produce accurate results. This research p...

Background: Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders in pregnancy, which is associated with serious complications. In the event of early diagnosis of this disease, some of the maternal and fetal complications can be prevented. The aim of this study was to early predict gestational diabetes mellitus by two statistical models including artificial neural ne...

For every oriented tree T there exists a graph DT (called the dual of T ) such that T 6→ G ⇔ G → DT holds for every G (an arrow denotes the existence of a homomorphism). An explicit construction of DT has been found recently. Although the DT constructed this way may have exponential number of vertices in |V (T )| = n, we will prove that its diameter is linear in n (and therefore DT is ”small” i...

In recent years, machine learning is attaining higher precision and accuracy in clinical heart disease dataset classification. However, literature shows that the quality of feature used for training model has a significant impact on outcome predictive model. Thus, this study focuses exploring features performance prediction by employing recursive elimination with cross-validation (RFECV). Furth...

Text Categorization is the process of automatically assigning predefined categories to free text documents. Feature weighting, which calculates feature (term) values in documents, is one of important preprocessing techniques in text categorization. This paper is a comparative study of feature weighting methods in statistical learning of Thai Document Categorization Framework. Six methods were e...

BACKGROUND Implanting centers often require the identification of a dedicated caregiver before destination therapy left ventricular assist device (DT LVAD) implantation; however, the caregiver experience surrounding this difficult decision is relatively unexplored. METHODS AND RESULTS From October 2012 through July 2013, we conducted semistructured, in-depth interviews with caregivers of pati...

This work aimed to investigate the potential of remote sensing to provide information on the spatial distribution of habitats in the Alpine region. Specifically, the performances of different classification methods, namely Maximum Likelihood (ML), Decision Tree (DT) and Support Vector Machine (SVM) were investigated for land-cover mapping using multitemporal RapidEye data. Results showed that S...

In recent years, much governmental investment has been committed to R&D in the area of information technology industry. However, its commercialization rate is reported to be lower than expected. In order to prevent such waste, feedback information obtained from the rigorous evaluation of the finished R&D project needs to be utilized for future selection of new projects. The main purpose of our ...

Web classification has been attempted through many different technologies. In this study we concentrate on the comparison of Neural Networks (NN), Naïve Bayes (NB) and Decision Tree (DT) classifiers for the automatic analysis and classification of attribute data from training course web pages. We introduce an enhanced NB classifier and run the same data sample through the DT and NN classifiers ...

This paper presents an Hidden Markov Model (HMM)-based variable speech rate Mandarin Chinese text-to-speech (TTS) system. In this system, parameters of spectrum, fundametal frequency and state duration are generated by a context dependent HMM (CDHMM) whose model parameters are linear-interpolated from those of three CDHMMs trained by corpora in three different speech rates (SRs), i.e. fast, med...