#_*_conding:uft-8_*_
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Version:?0.0.1
Date:?2018-02-03
@Author:Cheney
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A?simple?case?to?predict?stock?price?rise/fall?according?to?four?Machine?Learning?models.
Analysis:?
I.???A?classifier?model?data?from?tushare?stock?data
II.??If?stock‘s?present?price?rising?compared?with?previous?day?mark?the?tag?direction?as?1?otherwise?tag?is?-1
III.?x_train/x_test?is?from?percentage?of?lagged?close?price?y_train/y_test?is?from?direction?value???
Reference?source:?http://blog.csdn.net/u013547284/article/details/78443712

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import?datetime
import?numpy?as?np
import?pandas?as?pd
import?sklearn
import?pandas_datareader?as?pdr
import?tushare?as?ts

from?sklearn.ensemble?import?RandomForestClassifier
from?sklearn.linear_model?import?LogisticRegression
from?sklearn.

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????目錄???????????0??2018-02-05?14:36??Quantitative-trading-master\
?????文件?????????926??2018-02-05?14:36??Quantitative-trading-master\README.md
?????文件????????3911??2018-02-05?14:36??Quantitative-trading-master\caseaa_stock_predict_ml.py
?????文件????????1512??2018-02-05?14:36??Quantitative-trading-master\quantitative_analysis.py
?????文件???????41430??2018-02-05?14:36??Quantitative-trading-master\quantitative_analysis_stocker.py