Machine Learning for Data Linkage

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, Information Retrieval, and Record Linkage

Classification into groups using terms available in the data underlies machine learning, information retrieval, and record linkage. Classifiers such as Bayesian networks in machine learning and term weighting in information retrieval depend primarily on training data sets for which truth is known. These classifiers may be relatively slow to adapt to new situations in which new data have charact...

Improving the Performance of Machine Learning Algorithms for Heart Disease Diagnosis by Optimizing Data and Features

Heart is one of the most important members of the body, and heart disease is the major cause of death in the world and Iran. This is why the early/on time diagnosis is one of the significant basics for preventing and reducing deaths of this disease. So far, many studies have been done on heart disease with the aim of prediction, diagnosis, and treatment. However, most of them have been mostly f...

Machine Learning and Data

Machine Learning for Sequential Data: A Review

Statistical learning problems in many fields involve sequential data. This paper formalizes the principal learning tasks and describes the methods that have been developed within the machine learning research community for addressing these problems. These methods include sliding window methods, recurrent sliding windows, hidden Markov models, conditional random fields, and graph transformer net...