We present in this paper the system submissions of the SDL Language Weaver team in the WMT 2012 Quality Estimation shared-task. Our MT quality-prediction systems use machine learning techniques (M5P regression-tree and SVM-regression models) and a feature-selection algorithm that has been designed to directly optimize towards the official metrics used in this shared-task. The resulting submissi...

This article presents a procedure for using machine vision data to predict surface roughness parameter of the end milled components. Stylus based surface roughness measurements were used and compared to vision based prediction of surface roughness. Wavelet decomposition was used to extract features from vision based data. In this article wavelet Energy features of approximations and details wer...

In the current paper, efficiency of three new standalone data-mining algorithms [M5 Prime (M5P), Random Forest (RF), M5Rule (M5R)] and six novel hybrid bagging (BA-M5P, BA-RF BA-M5R) Attribute Selected Classifier (ASC-M5P, ASC-RF ASC-M5R) for streamflow prediction were assessed compared with an autoregressive integrated moving average (ARIMA) model as a benchmark. The models used precipitation ...

Combined use of new geospatial techniques and non-parametric multivariate statistical methods enables monitoring and quantification of the biomass of large areas of forest ecosystems with acceptable reliability. The main objective of the present study was to estimate the aboveground forest biomass (AGB) in the Sierra Madre Occidental (SMO) in the state of Durango, Mexico, using the M5 model tre...

Phosphomevalonate kinase (PMK) phosphorylates mevalonate-5-phosphate (M5P) in the mevalonate pathway, which is the sole source of isoprenoids and steroids in humans. We have identified new PMK inhibitors with virtual screening, using autodock. Promising hits were verified and their affinity measured using NMR-based (1)H-(15)N heteronuclear single quantum coherence (HSQC) chemical shift perturba...

In this study we aimed to draw a big comparative picture of the state of the art machine learning approaches for the software effort estimation problem. For this purpose, several datasets which were obtained from Promise data repository were used for testing various machine learning techniques. The results showed that, decision trees or rule induction based classifiers (i.e. M5P trees) gave par...

Drought prediction is the most effective way to mitigate drought impacts. The current study examined ability of three renowned machine learning models, namely additive regression (AR), random subspace (RSS), and M5P tree, their hybridized versions (AR-RSS, AR-M5P, RSS-M5P, AR-RSS-M5P) in predicting standardized precipitation evapotranspiration index (SPEI) multiple time scales. SPEIs were calcu...

Abstract Drought is one of the major barriers to socio-economic development a region. To manage and reduce impact drought, drought vulnerability modelling important. The use an ensemble machine learning technique i.e. M5P, M5P -Dagging, M5P-Random SubSpace (RSS) M5P-rotation forest (RTF) assess maps (DVMs) for state Odisha in India was proposed first time. A total 248 drought-prone villages (sa...

In this study, morphometric features such as total length, standard length, and fork length obtained from a total of 321 Sparus aurata samples, including 164 females and 157 males, captured between 2012 and 2013 from İskenderun Bay were used as input value, while weight was used as an output value. The Artificial Neural Network (MLP-Multi-L Layer Perceptron) as well as the M5P algorithm and Lin...