The Forest Save File
In R, after running 'random forest' model, I can use save.image('.RData') to store the model. Afterwards, I can just load the model to do predictions directly.Can you do a similar thing in python? I separate the Model and Prediction into two files. And in Model file: rf= RandomForestRegressor(nestimators=250, maxfeatures=9,computeimportances=True)fit= rf.fit(Predx, Predy)I tried to return rf or fit, but still can't load the model in the prediction file.Can you separate the model and prediction using the sklearn random forest package? I use dill, it stores all the data and I think possibly module information? I remember trying to use pickle for storing these really complicated objects and it didn't work for me.
The Forest Save Files Download
The Forest Save File Download
CPickle probably does the same job as dill but i've never tried cpickle. It looks like it works in literally the exact same way. I use 'obj' extension but that's by no means conventional.It just made sense for me since I was storing an object. How to recover deleted notepad text. Import dillwd = '/whatever/you/want/your/working/directory/to/be/'rf= RandomForestRegressor(nestimators=250, maxfeatures=9,computeimportances=True)rf.fit(Predx, Predy)dill.dump(rf, open(wd + 'filename.obj','wb'))btw, not sure if you use iPython, but sometimes writing a file that way doesn't so you have to do the: with open(wd + 'filename.obj','wb') as f:dill.dump(rf,f)call the objects again: model = dill.load(open(wd + 'filename.obj','rb')).