Upload File

finding your way, courtesy of machine learningcs229.stanford.edu/proj2016spr/poster/055.pdffinding...

  • Home
  • Documents
  • Finding Your WAY, Courtesy of Machine Learningcs229.stanford.edu/proj2016spr/poster/055.pdfFinding Your WAY, Courtesy of Machine Learning Chaitanya Asawa1, Marcus Gomez1, Viraj Mehta2
1
Finding Your WAY, Courtesy of Machine Learning Chaitanya Asawa 1 , Marcus Gomez 1 , Viraj Mehta 2 1 Department of Computer Science, Stanford University, 2 Department of Mathematics, Stanford University • Undergraduates at Stanford must take 11 courses across 8 different WAYS • Currently, many Stanford courses are not assigned a WAY yet, even when they seemingly should • Given a course description, we would like to predict what WAY(S) it satisfies • This is a multi-label, multi-class problem. • Each WAY represents an output class • Each course can satisfy a single or multiple WAY(S), so there are multiple labels Future Direc*ons We think an important issue was the dearth of data available to us, and believe that our models can perform better with more data. ß2AR Hoping to capture nonlinear interactions between the words that our previous models may not have, we used deep learning sequential models, including a: • RNN – Recurrent Neural Net • LSTM – Long Short Term Memory Networks • GRU – Gated Recurrent Unit The inputs were course descriptions converted into a distributed vector representation using GloVe word vectors. Mo*va*on Problem Statement Dataset OneVsRest Support Vector Machines Background … Neural Sequen*al Models Generalized Recurrent Model • We received access to ExploreCourses data • We lowercased all words, removed stop words, and punctuation, and stemming in some cases • Out of 14336 courses gathered, only 1571 satisfied WAY(S) – very limited data for multiple labels and classes Leveraged linear and Gaussian kernels ROC curves for linear kernel SVM ROC curves for Gaussian kernel SVM Dimensionality Reduc*on with PCA Reduced model variance using first n principal components Percentage of variance explained by components by number of components used Error of linear PCA as a function of number of components used Independence BoosTexter Mod of AdaBoost for multi- class, multi-label problems BoosTexter exhibits a classic overfitting curve Linearity assumption is likely incorrect Covariance of WAYS frequencies Linear and Naïve-Bayes OneVsRest classifiers using Word2Vec-style negative case subsampling Say you would like to fulfill your Formal Reasoning WAY with “Complex Analysis, Geometry, and Topology.” Unfortunately, you can’t. Evalua*on Metric: Hamming Error Baseline Models Comparison of All Models Performance of different neural models Tuning GRU on output size does not have much effect

Upload: others

Post on 10-Jul-2020

3 views

Category:

Documents


0 download

Report

TRANSCRIPT

Page 1: Finding Your WAY, Courtesy of Machine Learningcs229.stanford.edu/proj2016spr/poster/055.pdfFinding Your WAY, Courtesy of Machine Learning Chaitanya Asawa1, Marcus Gomez1, Viraj Mehta2

Finding Your WAY, Courtesy of Machine Learning Chaitanya Asawa1, Marcus Gomez1, Viraj Mehta2

1 Department of Computer Science, Stanford University, 2 Department of Mathematics, Stanford University

•  Undergraduates at Stanford must take 11 courses across 8 different WAYS

•  Currently, many Stanford courses are not assigned a WAY yet, even when they seemingly should

•  Given a course description, we would like to predict what WAY(S) it satisfies

•  This is a multi-label, multi-class problem.•  Each WAY represents an output class•  Each course can satisfy a single or multiple WAY(S), so

there are multiple labels

FutureDirec*onsWe think an important issue was the dearth of data available to us, and believe that our models can perform better with more data.

ß2AR

Hoping to capture nonlinear interactions between the words that our previous models may not have, we used deep learning sequential models, including a:•  RNN – Recurrent Neural Net•  LSTM – Long Short Term Memory Networks•  GRU – Gated Recurrent UnitThe inputs were course descriptions converted into a distributed vector representation using GloVe word vectors.

Mo*va*on

ProblemStatement

Dataset

OneVsRestSupportVectorMachines

Background …

NeuralSequen*alModels

Generalized Recurrent Model

•  We received access to ExploreCourses data•  We lowercased all words, removed stop words, and

punctuation, and stemming in some cases•  Out of 14336 courses gathered, only 1571 satisfied

WAY(S) – very limited data for multiple labels and classes

Leveraged linear and Gaussian kernels

ROC curves for linear kernel SVM ROC curves for Gaussian kernel SVM

DimensionalityReduc*onwithPCAReduced model variance using first n principal components

Percentage of variance explained by components by number of components

used

Error of linear PCA as a function of number of components used

Independence BoosTexterMod of AdaBoost for multi-class, multi-label problems

BoosTexter exhibits a classic overfitting curve

Linearity assumption is likely incorrect

Covariance of WAYS frequencies

Linear and Naïve-Bayes OneVsRest classifiers using Word2Vec-style negative case subsampling

Say you would like to fulfill your Formal Reasoning WAY with “Complex Analysis, Geometry, and Topology.” Unfortunately, you can’t.

Evalua*onMetric:HammingError

BaselineModels

ComparisonofAllModelsPerformance of different neural models Tuning GRU on output size does not

have much effect

Courtesy of Jason NOT FOR RESALE - ibiblio military Techni… · Courtesy of Jason NOT FOR RESALE. Courtesy of Jason NOT FOR RESALE. Courtesy of Jason NOT FOR RESALE. Courtesy of

Zhu MOLECULAR PAIN RESEARCH Open Access Transforming ... · Yaohui Zhu1, Tugba Colak2, Mohan Shenoy2, Liansheng Liu1, Kshama Mehta2, Reetesh Pai4, Bende Zou3, Xinmin Simon Xie2,3

International Workshop on Multi-Phase Flows: Analysis ...APPLICATIONS IN FLUIDS, SOLIDS AND BIOMECHANICS Hector Gomez1 1 School of Mechanical Engineering, Purdue University Phase-

Courtesy Mass Appointment Verificationhr.fsu.edu/.../training/CourtesyMassAppointmentVerificationForm.pdf · Courtesy Mass Appointment Verification . Each year, many Courtesy appointments

Courtesy Translation

Microbial xylanases and their industrial application in pulp and … · 2017-08-26 · Abhishek Walia1 • Shiwani Guleria1 • Preeti Mehta2 • Anjali Chauhan3 • Jyoti Parkash4

Courtesy : RRB... Courtesy : RRB. Courtesy : RRB.

Logos Courtesy of and photo courtesy of

Courtesy 3

Courtesy - Archive

Common Courtesy

Photo courtesy of pleiade.org. Photo courtesy of apod.nasa.gov

of Courtesy

N messenger RNA stability - fulltext.calis.edu.cnfulltext.calis.edu.cn/nature/nature/505/7481/nature12730.pdf · Xiao Wang1, Zhike Lu1, Adrian Gomez1,GaryC.Hon2, Yanan Yue1, Dali

Courtesy eFinance

Model-Based Active Exploration - proceedings.mlr.pressproceedings.mlr.press/v97/shyam19a/shyam19a.pdfModel-Based Active Exploration Pranav Shyam 1Wojciech Jaskowski´ Faustino Gomez1

The Duty to Defend Has Its Limits - selmanlaw.com Article from SDL... · Valet parking courtesy of Flowers courtesy of Band courtesy of Dessert courtesy of Lanyards courtesy of

Internet Archive Nahi.pdf · Courtesy . Courtesy . Courtesy

Document Courtesy of the National Archives...Document Courtesy of the National Archives. Document Courtesy of the National Archives. Document Courtesy of the National Archives. Document

UNIVERSIDAD CATÓLICA DE COLOMBIA FACULTAD DE … · universidad catÓlica de colombia facultad de derecho. diego armando perez gomez1. articulo de grado. la contrataciÓn publica

Courtesy car.pdf

Courtesy  · Courtesy . Courtesy . Courtesy

BACTERIA Courtesy of: . PROTIST Courtesy of:

CroniconCronicon OPEN ACCESS EC CARDIOLOGY Review Article Basic Understanding of Supraventricular Tachycardia for Post Graduates Sachin Sondhi1*, Ayushi Mehta2, Vikas Banayal3 and

‘COURTESY in COMMUNITY’ Courtesy should be common in family life and marriage Courtesy should be common in the workplace [things run better] And courtesy

Courtesy of Fatwa - (eFatwa.Com) · PDF fileCourtesy of Fatwa - (eFatwa.Com) Courtesy of Fatwa - (eFatwa.Com) Courtesy of Fatwa - (eFatwa.Com)

Bilateral intraventricular mass in a childNeuropathology Education Bilateral intraventricular mass in a child Deepali Jain1 and Veer Singh Mehta2 1Department of Pathology, Sir Ganga

PORT COURTESY HANDBOOK - State · PORT COURTESY BASICS 2 WHAT IS A PORT COURTESY? A Port Courtesy or “Courtesy of the Port” provides Foreign Government Officials and their

Courtesy Courtesy . Courtesy . Courtesy

MILITARY COURTESY

EARTHQUAKE FORECASTING USING ARTIFICIAL NEURAL NETWORKS · 2018-11-27 · EARTHQUAKE FORECASTING USING ARTIFICIAL NEURAL NETWORKS Anmol Bhatia1, Sumanta Pasari1,, Anand Mehta2 1 Dept

Name of National Lab - energy.gov Industry... · Courtesy GRC Courtesy NREL Courtesy CPike /ACEP Courtesy RAM Power Courtesy NREL Courtesy GRC Geothermal Technologies Office . Eric

Atmospheric pollutants in peri-urban forests of Quercus ... · 3 Héctor García-Gomez1, Laura Aguillaume2, Sheila Izquieta-Rojano4, Fernando Valiño1, Anna Àvila3, David Elustondo4,

Courtesy NASA

Improvement for enhanced xylanase production by ...design of response surface methodology Abhishek Walia1 • Preeti Mehta2 • Shiwani Guleria3 • Chand Karan Shirkot3 Received: