# https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingClassifier.html
from sklearn.ensemble import GradientBoostingClassifier
#https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html
from sklearn.model_selection import train_test_split
import numpy
csvdata = numpy.loadtxt('sample.csv', delimiter=',', dtype='float')
#https://note.nkmk.me/python-numpy-loadtxt-genfromtxt-savetxt/
X, y = numpy.delete(csvdata, csvdata.shape[1]-1, 1), numpy.delete(csvdata, slice(csvdata.shape[1]-1), 1).reshape(-1)
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)
clf = GradientBoostingClassifier(n_estimators=100, learning_rate=1.0,
max_depth=1, random_state=0).fit(X_train, y_train)
clf.score(X_test, y_test)
