Deep Reinforcement Learning & Feature Extraction For Constructing Alpha Generating Equity Portfolios

2021 ◽  
Author(s):  
Alexander Fleiss ◽  
Amrith Kumaar ◽  
Adam Rida ◽  
Junsup Shin ◽  
Xinying Lai ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Reinforcement Learning ◽  
Equity Portfolios

Methodology for eliminating imbalance of image data sets

2021 ◽  
Vol 1 (2 (6)) ◽  
Author(s):  
Tatyana Biloborodova ◽  
Inna Skarga-Bandurova ◽  
Mark Koverga
Keyword(s):  
Feature Extraction ◽  
Reinforcement Learning ◽  
Key Words ◽  
Class Imbalance ◽  
Image Data ◽  
Unbalanced Data ◽  
Data Sets ◽  
Learning Technology ◽  
Data Set ◽  
Image Fragment

The methodology of solving the problem of eliminating class imbalance in image data sets is presented. The proposed methodology includes the stages of image fragment extraction, fragment augmentation, feature extraction, duplication of minority objects, and is based on reinforcement learning technology. The degree of imbalance indicator was used as a measure to determine the imbalance of the data set. An experiment was performed using a set of images of the faces of patients with skin rashes, annotated according to the severity of acne. The main steps of the methodology implementation are considered. The results of the classification showed the feasibility of applying the proposed methodology. The accuracy of classification on test data was 85%, which is 5% higher than the result obtained without the use of the proposed methodology. Key words: class imbalance, unbalanced data set, image fragment extraction, augmentation.

Image Quality-Driven Octorotor Flight Control via Reinforcement Learning

2018 ◽  
Author(s):  
Qiang Li ◽  
Yunjun Xu
Keyword(s):  
Image Analysis ◽  
Feature Extraction ◽  
Reinforcement Learning ◽  
Flight Control ◽  
Learning Method ◽  
Satisfactory Performance ◽  
Control Command ◽  
Command Generation ◽  
Learning Technique ◽  
The Relationship

This article presents the design of a reinforcement learning method based flight controller to enhance the qualities of image taken from an octorotor platform. Concerning the effect of a low resolution and a high blur rate of target images on feature extraction and target detection, we started by analyzing the relationship between these two kinds of image qualities and altitude and velocity of the octorotor. This leads to the generation of corresponding control commands. We then applied a reinforcement learning technique to automatically design the altitude and velocity controllers of the octorotor. The image analysis and the control command generation algorithms are successfully tested on the octorotor platform, and the controllers demonstrate a satisfactory performance in simulations.

Constructing Equity Portfolios from SEC 13F Data Using Feature Extraction and Machine Learning

2019 ◽  
Vol 2 (1) ◽  
pp. 45-60
Author(s):  
Alexander Fleiss ◽  
Han Cui ◽  
Sasha Stoikov ◽  
Daniel M. DiPietro
Keyword(s):  
Machine Learning ◽  
Feature Extraction ◽  
Equity Portfolios
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