A Web-Based User Interface for Machine Learning Analysis

  title={A Web-Based User Interface for Machine Learning Analysis},
  author={Fatma Nasoz and Chandani Shrestha},
The objective of this thesis is to develop a user friendly web application that will be used to analyse data sets using various machine learning algorithms. The application design follows human computer interaction design guidelines and principles to make a user friendly interface [Shn03]. It uses Linear Regression, Logistic Regression, Backpropagation machine learning algorithms for prediction. This application is built using Java, Play framework, Bootstrap and IntelliJ IDE. Java is used in… 
Facilitating and Managing Machine Learning and Data Analysis Tasks in Big Data Environments using Web and Microservice Technologies
The performance of the new framework is evaluated on state-of-the-arts machine learning algorithms: it is shown that storing and retrieving machine learning models as well as a respective acceptable low overhead demonstrate an efficient approach to facilitate machine learning in big data environments.
Transactions on Large-Scale Data- and Knowledge-Centered Systems XLV: Special Issue on Data Management and Knowledge Extraction in Digital Ecosystems
The key limitations faced by organisations in need for efficiently accessing and managing data over DLTs are introduced and Datachain, a lightweight, flexible and interoperable framework deliberately designed to ease the extraction of data hosted on DLTs, is introduced.


Introduction to machine learning
  • Ethem Alpaydin
  • Computer Science
    Adaptive computation and machine learning
  • 2004
Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts, and discusses many methods from different fields, including statistics, pattern recognition, neural networks, artificial intelligence, signal processing, control, and data mining.
Characterization of the Wisconsin Breast cancerDatabase Using a Hybrid Symbolic -
A new rule ordering and evaluation algorithm that orders extracted rules based on three performance measures so they can be used by any generic inference engine and can be applied to any static classiication problem with numerical or categorical inputs.
Scaling up the Naive Bayesian Classifier : Using Decision Trees for Feature Selection
A Selective Bayesian classifier that simply uses only those features that C4.5 would use in its decision tree when learning a small example of a training set, a combination of the two different natures of classifiers is described.
Neural Networks and Learning Machines
Refocused, revised and renamed to reflect the duality of neural networks and learning machines, this edition recognizes that the subject matter is richer when these topics are studied together.
The Elements of User Experience: User-Centered Design for the Web
This chapter introduces the five Planes of User Experience, and discusses the role of interface design, navigation design, information architecture, and strategy in the development of user experience.
Gaussian Processes for Machine Learning
The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics, and deals with the supervised learning problem for both regression and classification.
An Implementation of Logical Analysis of Data
An implementation of this "logical analysis of data" (LAD) methodology is described, along with the results of numerical experiments demonstrating the classification performance of LAD in comparison with the reported results of other procedures.
Machine Learning in Medical Applications
It is argued that the successful implementation of ML methods can help the integration of computer-based systems in the healthcare environment providing opportunities to facilitate and enhance the work of medical experts and ultimately to improve the efficiency and quality of medical care.