from sklearn.model_selection import cross_val_score
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from plotter import plot_cross_validation
from sklearn import datasets
import warnings
warnings.filterwarnings('ignore')
#------------------
digits = datasets.load_digits()
X = digits.data
Y = digits.target
clf = LinearDiscriminantAnalysis()
clf.fit(X, Y)
n = 1
print(clf.predict(X[1:10]))
print((X[1:3]))
print(cross_val_score(clf, X, Y, cv=10))
print("Сравнение показателей ...")
plot_cross_validation(X=X, y=Y, clf=clf, title="Linear Discriminant Analysis")
from sklearn.naive_bayes import GaussianNB
from sklearn.model_selection import cross_val_score
from plotter import plot_cross_validation
from sklearn import datasets
import warnings
warnings.filterwarnings('ignore')
#------------------
data = datasets.load_iris()
X=data.data
Y=data.target
clf = GaussianNB()
partial = clf.partial_fit
print(partial)
clf.fit(X, Y)
print(clf.predict(X[:5]))
print((X[:5]))
print(clf.partial_fit)
print(cross_val_score(clf, X, Y, cv=10))
print("Сравнение показателей ...")
plot_cross_validation(X=X, y=Y, clf=clf, title="Gaussian Naive Bayes")