classification_crypto_class_report.py

# Other models
from sklearn.ensemble import AdaBoostClassifier, GradientBoostingClassifier, RandomForestClassifier
from sklearn.neighbors import KNeighborsClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.naive_bayes import GaussianNB
from sklearn.svm import SVC
from sklearn.tree import DecisionTreeClassifier

models = {
    "adaboost":AdaBoostClassifier(random_state=11), 
    "gradboost":GradientBoostingClassifier(random_state=11), 
    "rf":RandomForestClassifier(random_state=11), 
    "knn":KNeighborsClassifier(),
    "logreg":LogisticRegression(solver='liblinear'), 
    "nb":GaussianNB(), 
    "svm":SVC(),
    "dec_tree": DecisionTreeClassifier()
}

for model_name, model in models.items():
    
    # Fitting 
    clf = model
    
    clf.fit(X_train, y_train)
    
    # Predictions
    preds = clf.predict(X_test)

    #Printing out results
    report = classification_report(y_test, preds)
    print(model_name+"\n",report)