1、需求及数据集说明
这是一项二分类任务,评估的是分类准确性(正确预测的标签百分比)。训练集有1000个样本,测试集有9000个样本。你的预测应该是一个9000 x 1的向量。您还需要一个Id列(1到9000),并且应该包括一个标题。格式如下所示:
Id,Solution
1,0
2,1
3,1
...
9000,0
数据集下载地址
链接:https://pan.baidu.com/s/1Dy5uF_OAmCQC3G-71e-yEQ?pwd=tjzq
提取码:tjzq
2、导入包、读取数据
import numpy as np
import pandas as pd
from sklearn.metrics import accuracy_score
from sklearn.model_selection import cross_val_score
import os
train_data = pd.read_csv('../input/train.csv',header = None)
train_labels = pd.read_csv('../input/trainLabels.csv',header = None)
test_data = pd.read_csv('../input/test.csv',header = None)
如果下面的模型运行时报错,可以试下面的写法
train_data = pd.read_csv('data-science-london-scikit-learn/train.csv',header