Regularized Linear Regression and Bias v.s. Variance

Introduction

• implement regularized linear regression and use it to study models with different bias-variance properties.

Files included in this exercise

• ex5.m - Octave/MATLAB script that steps you through the exercise
• ex5data1.mat - Dataset
• submit.m - Submission script that sends your solutions to our servers
• featureNormalize.m - Feature normalization function
• fmincg.m - Function minimization routine (similar to fminunc)
• plotFit.m - Plot a polynomial t
• trainLinearReg.m - Trains linear regression using your cost function
• [?] linearRegCostFunction.m - Regularized linear regression cost function
• [?] learningCurve.m - Generates a learning curve
• [?] polyFeatures.m - Maps data into polynomial feature space
• [?] validationCurve.m - Generates a cross validation curve
• ? indicates les you will need to complete

IDE : Octave_4.4.0

ex5.zip