from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import cross_val_score
forest = RandomForestClassifier(n_estimators=30, class_weight='balanced')

x = encoded[[c for c in encoded.columns if 'snp' in c]].values
y = classes.values

scores = cross_val_score(forest, x, y, cv=5)
scores.mean(), scores.std()

# (0.53006376086711415, 0.25595331741742744)