# a pipeline for quick data analysis and machine learning
## file_operate:
* read file and do base operate like auto asdtype etc.
* it support multi type files operates together.
## preprocess:
create a preprocessor to preprocessing(dropna,fillna,dropoutlyers...)
you can select the file and cols by passing dict-type args.
## analysis:
base on the previous manipulations,we get clean datas,we can now acutally start the analysis tasks:
correlation:
get correlations between value-type features and labels.
compare the correlation between class-type features and labels.
## modeling:
we provide base ml models to complete classification or regression tasks
listing:
gbdt:xgboost,light gbm,radom forests
norm:svc,linear,logistic,bayes
timesequence:ARMA,ARIMA
nn:
DeepLearning:\
## statistic_test:
[//]: # ( [test func](https://blog.csdn.net/weixin_46271668/article/details/123981051))
normality test
correlation test
significance test
parametric test
nonparametric test
Raw data
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"description": "# a pipeline for quick data analysis and machine learning\r\n\r\n## file_operate:\r\n\r\n* read file and do base operate like auto asdtype etc.\r\n* it support multi type files operates together.\r\n\r\n## preprocess:\r\n\r\n create a preprocessor to preprocessing(dropna,fillna,dropoutlyers...)\r\n you can select the file and cols by passing dict-type args.\r\n## analysis:\r\n base on the previous manipulations,we get clean datas,we can now acutally start the analysis tasks:\r\n correlation:\r\n get correlations between value-type features and labels. \r\n compare the correlation between class-type features and labels.\r\n \r\n\r\n## modeling:\r\n we provide base ml models to complete classification or regression tasks\r\n listing:\r\n gbdt:xgboost,light gbm,radom forests\r\n norm:svc,linear,logistic,bayes\r\n timesequence:ARMA,ARIMA\r\n nn:\r\n DeepLearning:\\\r\n\r\n## statistic_test:\r\n\r\n[//]: # ( [test func](https://blog.csdn.net/weixin_46271668/article/details/123981051))\r\n\r\n normality test\r\n correlation test\r\n significance test\r\n parametric test\r\n nonparametric test\r\n",
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