Combining Synthetic and Observed Data to Enhance Machine Learning Model Performance for Streamflow Prediction

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...

Impacts of combining meteorological and hydrometric data on the accuracy of streamflow modeling

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...

Combining Data Mining and Machine Learning for Effective Fraud Detection

This paper describes the automatic design of methods for detecting fraudulent behavior. Much of the design is accomplished using a series of machine learning methods. In particular, we combine data mining and constructive induction with more standard machine learning techniques to design methods for detecting fraudulent usage of cellular telephones based on profiling customer behavior. Specific...

Combining Data Mining and Machine Learning for Effective User Profiling

This paper describes the automatic design of methods for detecting fraudulent behavior. Much of the de&,, ic nrrnm,-,li~h~rl ,,&,a n .am.L~ nf mn.-h;na lm..~:~~ e-. .. ..--..*.*yYYA’“.. UY.“b Y UISLUY “I III-Yllr IxuIY11~ methods. In particular, we combine data mining and constructive induction with more standard machine learning techniques to design methods for detecting fraudulent usage of ce...