Indians_xgboost.py

# -*- coding: utf-8 -*-
"""
Created on Wed Jan 09 14:12:47 2019

@author: XIAO RUI
"""

from numpy import loadtxt
from xgboost import XGBClassifier
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score

dataset = loadtxt('dataset_001.csv', delimiter=",")
X = dataset[:,0:8]
Y = dataset[:,8]

seed = 7
test_size = 0.33
X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=test_size, random_state=seed)

# 不可视化数据集
#model = XGBClassifier()
#model.fit(X_train, y_train)

##可视化测试集的loss
model = XGBClassifier()
eval_set = [(X_test, y_test)]
model.fit(X_train, y_train, early_stopping_rounds=10, eval_metric="logloss", eval_set=eval_set, verbose=True)

y_pred = model.predict(X_test)
predictions = [round(value) for value in y_pred]

accuracy = accuracy_score(y_test, predictions)
print("Accuracy: %.2f%%" % (accuracy * 100.0))