K-Means algorithm does not require the establishment of the model after the new prediction of the results, there is no corresponding tag, but only on the characteristics of data clustering data. The principal component analysis reduces the dimension, carries on the visualization operation to the data, reduces the dimension to the features.

Homework3\computeCentroids.m
Homework3\displayData.m
Homework3\drawLine.m
Homework3\ex3.m
Homework3\ex3data1.mat
Homework3\ex3data2.mat
Homework3\ex3_pca.m
Homework3\featureNormalize.m
Homework3\findClosestCentroids.m
Homework3\Homework3.docx
Homework3\kMeansInitCentroids.m
Homework3\pca.m
Homework3\plotDataPoints.m
Homework3\plotProgresskMeans.m
Homework3\projectData.m
Homework3\recoverData.m
Homework3\runkMeans.m
Homework3\~$mework3.docx
Homework3

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