Machine-Learning Studies on Spin Models

Dust source mapping using satellite imagery and machine learning models

Predicting dust sources area and determining the affecting factors is necessary in order to prioritize management and practice deal with desertification due to wind erosion in arid areas. Therefore, this study aimed to evaluate the application of three machine learning models (including generalized linear model, artificial neural network, random forest) to predict the vulnerability of dust cent...

Machine Learning Models for Housing Prices Forecasting using Registration Data

This article has been compiled to identify the best model of housing price forecasting using machine learning methods with maximum accuracy and minimum error. Five important machine learning algorithms are used to predict housing prices, including Nearest Neighbor Regression Algorithm (KNNR), Support Vector Regression Algorithm (SVR), Random Forest Regression Algorithm (RFR), Extreme Gradient B...

Machine Learning Models on Random Graphs

Survey on Machine Transliteration and Machine Learning Models

Globalization and growth of Internet users truly demands for almost all internet based applications to support local languages. Support of local languages can be given in all internet based applications by means of Machine Transliteration and Machine Translation. This paper provides the thorough survey on machine transliteration models and machine learning approaches used for machine transliter...

Debugging Machine Learning Models

Creating a machine learning solution for a real world problem often becomes an iterative process of training, evaluation and improvement where the best practices and generic solutions are few and far between. Our work presents a novel solution for an essential step of this cycle: the process of understanding the root causes of ’bugs’ (particularly consequential or confusing test errors) discove...