Comparative Analysis of Machine Learning Algorithms with Optimization Purposes

Comparative Analysis of Machine Learning Algorithms for Audio Signals Classification

ABSTARCT Research in the area of Audio Classification and retrieval, in comparison with closely related areas, such as speech recognition and speaker identification is relatively new Audio Classification is an important issue in current audio processing and content analysis researches.. Generally speaking, audio classification is a pattern recognition problem. Pattern recognition is the scienti...

Machine learning algorithms in air quality modeling

Modern studies in the field of environment science and engineering show that deterministic models struggle to capture the relationship between the concentration of atmospheric pollutants and their emission sources. The recent advances in statistical modeling based on machine learning approaches have emerged as solution to tackle these issues. It is a fact that, input variable type largely affec...

Practical Bayesian Optimization of Machine Learning Algorithms

The use of machine learning algorithms frequently involves careful tuning of learning parameters and model hyperparameters. Unfortunately, this tuning is often a “black art” requiring expert experience, rules of thumb, or sometimes bruteforce search. There is therefore great appeal for automatic approaches that can optimize the performance of any given learning algorithm to the problem at hand....

Spatiotemporal Estimation of PM2.5 Concentration Using Remotely Sensed Data, Machine Learning, and Optimization Algorithms

PM 2.5 (particles <2.5 μm in aerodynamic diameter) can be measured by ground station data in urban areas, but the number of these stations and their geographical coverage is limited. Therefore, these data are not adequate for calculating concentrations of Pm2.5 over a large urban area. This study aims to use Aerosol Optical Depth (AOD) satellite images and meteorological data from 2014 to 2017 ...

Annotating mobile phone location data with activity purposes using machine learning algorithms

A Comparative Study of Training Algorithms for Supervised Machine Learning

Classification in data mining has gained a lot of importance in literature and it has a great deal of application areas from medicine to astronomy, from banking to text classification.. It can be described as supervised learning algorithm as it assigns class labels to data objects based on the relationship between the data items with a pre-defined class label. The classification techniques are ...