Classifier Comparison.py

#Import and create all models. Tune appropiate parameters for each model
from sklearn.tree import DecisionTreeClassifier
tree = DecisionTreeClassifier(max_depth=4,random_state=0)
 
from sklearn.linear_model import LogisticRegression 
logreg = LogisticRegression(C=10)
 
from sklearn.neighbors import KNeighborsClassifier 
knn = KNeighborsClassifier(n_neighbors=1)
 
from sklearn.naive_bayes import BernoulliNB
naive_b = BernoulliNB(alpha=1)
 
from sklearn.ensemble import RandomForestClassifier
forest = RandomForestClassifier(n_estimators=100, random_state=42)
 
from sklearn.ensemble import GradientBoostingClassifier
gbrt = GradientBoostingClassifier(random_state=0, max_depth=1, learning_rate=0.1)
 
from sklearn.neural_network import MLPClassifier
mlp = MLPClassifier(solver='adam', random_state=42)
 
from sklearn.svm import SVC
svc = SVC(C=100, probability=True)
 
 
model_list=[tree,logreg,knn,naive_b,forest,gbrt,mlp,svc]