I need an equation for random forest so that I can score fresh data I receive every week, based on beta estimates I got after building model using this ensemble methodology.
Every week I do not want to build random forest model again and then score it using following commands in Python. Because I have build 15 such models and I need to score them every week. So easiest way is to get the equation (betas I already have) and score.
# importing the ensemble libraries
from `numpy` import `genfromtxt`
from `sklearn.metrics` import `classification_report`
#importing the dataset
dataset = genfromtxt(open('~//win_5050_6oct.csv','r'))[1:]
target = [x[1] for x in dataset]
train = [x[2:] for x in dataset]
test = genfromtxt(open('~\\win_act_6oct.csv','r'))[1:]
val = [x[2:] for x in test]
y_act = [x[1] for x in test]
Gst_i=[x[0] for x in test]
#building random forest model
rf = RandomForestClassifier(n_estimators=100)
rf.fit(train, target)