import numpy as np
import sklearn
from sklearn.svm import SVC
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
import catboost

import os
from matplotlib import pyplot as plt

divorce = np.loadtxt("divorce.csv", delimiter=";", skiprows=1)

Xtrain, Xtest, ytrain, ytest = train_test_split(divorce[:,0:-1], divorce[:,-1], train_size=.1)

clf = catboost.CatBoostClassifier(depth=5, learning_rate=.01, verbose=1)
pool = catboost.Pool(data=Xtrain, label=ytrain)

clf.fit(pool)

test_pool = catboost.Pool(data=Xtest)

predy = clf.predict(test_pool)

print("CatBoost: " + str(accuracy_score(ytest, predy)))

b8e569bdb328b92cee5e63bcb3f45963e97cfcf2
<mask token>

<mask token>
clf.fit(pool)
<mask token>
print('CatBoost: ' + str(accuracy_score(ytest, predy)))

<mask token>
divorce = np.loadtxt('divorce.csv', delimiter=';', skiprows=1)
Xtrain, Xtest, ytrain, ytest = train_test_split(divorce[:, 0:-1], divorce[:,
    -1], train_size=0.1)
clf = catboost.CatBoostClassifier(depth=5, learning_rate=0.01, verbose=1)
pool = catboost.Pool(data=Xtrain, label=ytrain)
clf.fit(pool)
test_pool = catboost.Pool(data=Xtest)
predy = clf.predict(test_pool)
print('CatBoost: ' + str(accuracy_score(ytest, predy)))

import numpy as np
import sklearn
from sklearn.svm import SVC
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
import catboost
import os
from matplotlib import pyplot as plt
divorce = np.loadtxt('divorce.csv', delimiter=';', skiprows=1)
Xtrain, Xtest, ytrain, ytest = train_test_split(divorce[:, 0:-1], divorce[:,
    -1], train_size=0.1)
clf = catboost.CatBoostClassifier(depth=5, learning_rate=0.01, verbose=1)
pool = catboost.Pool(data=Xtrain, label=ytrain)
clf.fit(pool)
test_pool = catboost.Pool(data=Xtest)
predy = clf.predict(test_pool)
print('CatBoost: ' + str(accuracy_score(ytest, predy)))

import numpy as np
import sklearn
from sklearn.svm import SVC
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
import catboost

import os
from matplotlib import pyplot as plt

divorce = np.loadtxt("divorce.csv", delimiter=";", skiprows=1)

Xtrain, Xtest, ytrain, ytest = train_test_split(divorce[:,0:-1], divorce[:,-1], train_size=.1)

clf = catboost.CatBoostClassifier(depth=5, learning_rate=.01, verbose=1)
pool = catboost.Pool(data=Xtrain, label=ytrain)

clf.fit(pool)

test_pool = catboost.Pool(data=Xtest)

predy = clf.predict(test_pool)

print("CatBoost: " + str(accuracy_score(ytest, predy)))
