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Full-Text Articles in Physical Sciences and Mathematics
Efficient Algorithms And Human-In-The-Loop Approaches For Attribute Design And Selection, Md Abdus Salam
Efficient Algorithms And Human-In-The-Loop Approaches For Attribute Design And Selection, Md Abdus Salam
Computer Science and Engineering Dissertations
Feature engineering and feature selection are two important aspects of data science pipeline. Due to the advancement of data collection techniques in recent years, huge amount of data is becoming available in different industries. Consequently, the importance of data science is increasing for business analytic purpose. Different tools and techniques are being developed to assist data scientists to complete their tasks efficiently. One of the main human involvements in the data science task is for feature engineering and selection. These pre-processing steps will prepare the data in the format desired to be fed into various machine learning algorithms to accomplish …
Feature Selection And Data Reconstruction Via Robust And Flexible Learning Models, Di Ming
Feature Selection And Data Reconstruction Via Robust And Flexible Learning Models, Di Ming
Computer Science and Engineering Dissertations
Feature selection and data reconstruction are very important topics in machine learning area. In today's big data environment, many data could have high dimensions and come with noise, corruption, etc. Thus, we develop robust and flexible learning models so as to select the relevant features from the high-dimensional data spaces and reconstruct the original clean data from the corrupted input data more efficiently and more effectively. To resolve the inflexibility of the widely used class-shared feature selection methods such as L21-norm, we derive LASSO from probabilistic selection on ridge regression which provides an independent point of view from the usual …