principal component analysis python pandas

Python3 Learning API UsagePrincipal component analysis method for reducing dimensionUsing the data set on the network, I have downloaded to the local, can go to my git referenceGit:https://github.com/linyi0604/machinelearningCode:1 fromSklearn.svmImportlinearsvc2 fromSklearn.metricsImportClassification_report3 fromSklearn.decompositionImportPCA4 ImportPandas as PD5 ImportNumPy as NP6 " "7

._clean_fields () self._clean_form () Self._post_clean ( )Start validation field: Self._clean_fields ()def _clean_fields (self):#循环字段, the field that is set in the form component, which is from the __new__ of Declarativefieldsmetaclass forName, fieldinchSelf.fields.items (): # value_from_datadict () gets the data fromThe data dictionaries. # Each widget type knows what to retrieve it own data, because some # widgets split data over several HTML Fiel

Auther: zfive5 (zhaozidong)Email: zfive5@yahoo.com.cnDatetime: 2004-12-10 02:20:00 I was asleep now, but it was hard to fall asleep due to a severe toothache. I had to open the machine and write something, so I learned to studyCOM component usage!First, write a simple COM component using VC, Vc idl and class definition: # Pragma once# Include "resource. H" // main symbol // Iizfive5[Object,UUID ("808d04aa-c