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How to use string features in random forest for real-time big data


Random forest on a big datasetRandom Forest by R package party overfits on random dataHow to tackle classification with string features?Using KDDCup 99 Data with Spark MLLib RandomForestHow to handle categorical features for Decision Tree, Random Forest in spark ml?Feature selection using Random forest with importance / varImp functions with factor variablesReal time Openscoring Bad request for Linear Regression modelWeka Random Forest model file size is too bigIs Isolation Forest (iForest) a method that could be directly applied to Big Data?How to implement random forest algorithm from scratch in C++






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I have a huge dataset that needs to run a binary classification on it. Some features in the dataset are string, so cannot use them without converting to numeric values. I tried fit_transform and applied the RandomForest after and worked properly.
However, we are implementing a real-time system that time is a big issue! fit_transform is time-consuming. Any idea of how I can use string values or other libraries to convert string to digit as quickly as possible?
I also have access to Spark so if MLlib has something that can help please let me know!










share|improve this question




























    0















    I have a huge dataset that needs to run a binary classification on it. Some features in the dataset are string, so cannot use them without converting to numeric values. I tried fit_transform and applied the RandomForest after and worked properly.
    However, we are implementing a real-time system that time is a big issue! fit_transform is time-consuming. Any idea of how I can use string values or other libraries to convert string to digit as quickly as possible?
    I also have access to Spark so if MLlib has something that can help please let me know!










    share|improve this question
























      0












      0








      0








      I have a huge dataset that needs to run a binary classification on it. Some features in the dataset are string, so cannot use them without converting to numeric values. I tried fit_transform and applied the RandomForest after and worked properly.
      However, we are implementing a real-time system that time is a big issue! fit_transform is time-consuming. Any idea of how I can use string values or other libraries to convert string to digit as quickly as possible?
      I also have access to Spark so if MLlib has something that can help please let me know!










      share|improve this question














      I have a huge dataset that needs to run a binary classification on it. Some features in the dataset are string, so cannot use them without converting to numeric values. I tried fit_transform and applied the RandomForest after and worked properly.
      However, we are implementing a real-time system that time is a big issue! fit_transform is time-consuming. Any idea of how I can use string values or other libraries to convert string to digit as quickly as possible?
      I also have access to Spark so if MLlib has something that can help please let me know!







      bigdata real-time random-forest






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Mar 25 at 1:09









      Neda EbrahimiNeda Ebrahimi

      104




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