useful urls
摘要：
数据挖掘技术： http://ddl.escience.cn/f/IwoF?rid=8188575 李航 统计学习方法： http://ddl.escience.cn/f/Iwn0 阅读全文
posted @ 2018-12-19 10:43 Aimee0207 阅读(80) 评论(0) 推荐(0) 编辑
我的代码-flask
摘要：
import pickleimport flaskimport pandas as pdimport jsonfrom flask import Flaskfrom flask import request, render_template from sklearn.externals import 阅读全文
posted @ 2018-12-19 10:32 Aimee0207 阅读(178) 评论(0) 推荐(0) 编辑
我的代码-sql query
摘要：
# coding: utf-8 # In[ ]: WITH List AS (SELECT e.*,f.* FROM( SELECT DISTINCT c.lot_id, c.wafer_key,LEFT(c.layer_id, CHARINDEX('_', c.layer_id) -1) as L 阅读全文
posted @ 2018-12-19 10:29 Aimee0207 阅读(117) 评论(0) 推荐(0) 编辑
我的代码-unsupervised learning
摘要：
# coding: utf-8 # In[1]: import pandas as pdimport numpy as npfrom sklearn import treefrom sklearn.svm import SVCfrom sklearn.grid_search import GridS 阅读全文
posted @ 2018-12-19 10:27 Aimee0207 阅读(109) 评论(0) 推荐(0) 编辑
我的代码-statistic analysis
摘要：
# coding: utf-8 # In[1]: # numpy and pandas for data manipulationimport numpy as npimport pandas as pd # sklearn preprocessing for dealing with catego 阅读全文
posted @ 2018-12-19 10:26 Aimee0207 阅读(193) 评论(0) 推荐(0) 编辑
我的代码-test models
摘要：
# coding: utf-8 # In[2]: import pandas as pdimport numpy as npfrom sklearn.preprocessing import binarizefrom sklearn.preprocessing import LabelEncoder 阅读全文
posted @ 2018-12-19 10:26 Aimee0207 阅读(124) 评论(0) 推荐(0) 编辑
我的代码- rf sampling
摘要：
# coding: utf-8 # In[6]: import pandas as pdimport numpy as npfrom sklearn import treefrom sklearn.svm import SVCfrom sklearn.grid_search import GridS 阅读全文
posted @ 2018-12-19 10:25 Aimee0207 阅读(137) 评论(0) 推荐(0) 编辑
我的代码-normalize
摘要：
# coding: utf-8 # In[13]: import pandas as pdimport numpy as npimport scipy as spfrom os import listdirfrom os.path import isfile, joinfrom . import c 阅读全文
posted @ 2018-12-19 10:24 Aimee0207 阅读(120) 评论(0) 推荐(0) 编辑
我的代码-random forest
摘要：
# coding: utf-8 # In[1]: import pandas as pdimport numpy as npfrom sklearn import treefrom sklearn.svm import SVCfrom sklearn.grid_search import GridS 阅读全文
posted @ 2018-12-19 10:24 Aimee0207 阅读(291) 评论(0) 推荐(0) 编辑
