import sys
import os
sys.path.insert(0, os.path.abspath('..'))
from utility.sklearnbasemodel import BaseModel
import numpy as np
from sklearn.ensemble import AdaBoostRegressor
class AdaBoostModel(BaseModel):
def __init__(self):
BaseModel.__init__(self)
self.usedFeatures = [1,4,5,6,7]
self.randomSate = None
self.excludeZerosActual = True
return
def setClf(self):
# min_samples_split = 3
self.clf = AdaBoostRegressor()
return
def getTunedParamterOptions(self):
tuned_parameters = [{'min_samples_split': np.arange(2, 1000, 1)}]
# tuned_parameters = [{'min_samples_split': [5, 8,10,12]}]
# tuned_parameters = [{'min_samples_split': [5, 10]}]
return tuned_parameters
if __name__ == "__main__":
obj= AdaBoostModel()
obj.run()
