MakeML : automated machine learning from data to predictions
Name
1078154256-MIT.pdf
Description
Full printable version
Size
1.68 MB
Format
Adobe PDF
Checksum (MD5)
8e54839f27ecf28d9506b91384fad37e
Author(s)
Tromba, Isabella M
Advisor(s)
Sam Madden.
Alternative Title
Automated machine learning from data to predictions
Date Issued
2018
Publisher
Massachusetts Institute of Technology
Abstract
MakeML is a software system that enables knowledge workers with no programming experience to easily and quickly create machine learning models that have competitive performance with models hand-built by trained data scientists. MakeML consists of a web-based application similar to a spreadsheet in which users select features and choose a target column to predict. MakeML then automates the process of feature engineering, model selection, training, and hyperparameter optimization. After training, the user can evaluate the performance of the model and can make predictions on new data using the web interface. We show that a model generated automatically using MakeML is able to achieve accuracy better than 90% of submissions for the Titanic problem on the public data science platform Kaggle.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 61-64).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
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