生存预测 : kaggle titanic 泰坦尼克号 逻辑回归(Logistic回归) tensorflow版

目录

• test.csv
• train.csv
• titanic.py

数据集

https://www.kaggle.com/c/titanic/data

titanic.py

import tensorflow as tf
import pandas as pd

TRAIN_PATH = "train.csv"
TEST_PATH = "test.csv"
LEARNING_RATE = 0.01 # 0.01
EPOCH_NUM = 15 # 15
BATCH_SIZE = 100 # 100
LOGS_PATH = 'tensorboard_logs'
'''
PassengerId => 乘客ID
Pclass => 乘客等级(1/2/3等舱位)
Name => 乘客姓名
Sex => 性别
Age => 年龄
SibSp => 堂兄弟/妹个数
Parch => 父母与小孩个数
Ticket => 船票信息
Fare => 票价
Cabin => 客舱
Embarked => 登船港口
'''

def preprocess_data(path, is_test=False):
    data = pd.read_csv(path, index_col='PassengerId')
    data.drop(['Name', 'Ticket', 'Cabin'], axis=1, inplace=True)
    if is_test:
        data = data.replace([None], [0])
    else:
        data = data[pd.notnull(data['Age'])]
        data = data[pd.notnull(data['Embarked'])]
    data.replace(["female", "male"], [0, 1], inplace=True)
    data.replace(["Q", "C", "S"], [0