Kaggle Titanic 0.78468

次のプログラムを改造しました。

Kaggle Titanic 0.62200

そして、次の結果を得ました。

次のページを参考にしました。
Kaggle超初心者向け】Titanicにチャレンジしてみた

titanic03.py

#! /usr/bin/python
#
#   titanic03.py
#
#                   Mar/22/2020
# --------------------------------------------------------------------------
import sys
import pandas as pd
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import  train_test_split
from sklearn.metrics import (roc_curve , auc ,accuracy_score)
# --------------------------------------------------------------------------
# [4-2]:
def convert_proc(df):
    df['Fare'] = df['Fare'].fillna(df['Fare'].median())
    df['Age'] = df['Age'].fillna(df['Age'].median())
    df['Embarked'] = df['Embarked'].fillna('S')

    df['Sex'] = df['Sex'].apply(lambda x: 1 if x == 'male' else 0)
    df['Embarked'] = df['Embarked'].map( {'S': 0 , 'C':1 , 'Q':2}).astype(int)
#
    df = df.drop(['Cabin','Name','PassengerId','Ticket'],axis =1)
#
    return df
# --------------------------------------------------------------------------
# [4]:
def read_train_proc():
    train_df = pd.read_csv("train.csv", header=0)
#
    train_df = convert_proc(train_df)
#
    return  train_df

# --------------------------------------------------------------------------
# [6]:
def read_test_proc():
    test_df = pd.read_csv("test.csv", header=0)
    ids = test_df["PassengerId"].values
#
    test_df = convert_proc(test_df)
#
    return ids,test_df
# --------------------------------------------------------------------------
# [10]:
def submit_proc(ids,output):
    file_submit = "titanic_submit.csv"
#
    dft = pd.DataFrame({'PassengerId': ids, 'Survived': output})
    dft.to_csv(file_submit,index=False)
# --------------------------------------------------------------------------
# [8]:
def predict_proc(train_df,test_df):
#
    train_X = train_df.drop('Survived',axis = 1)
    train_y = train_df.Survived
#
    (train_X , test_X , train_y , test_y) = train_test_split(train_X, train_y , test_size = 0.3 , random_state = 0)
#
    clf = RandomForestClassifier(n_estimators = 10,max_depth=5,random_state = 0)
    clf = clf.fit(train_X , train_y)
    pred = clf.predict(test_X)
    fpr, tpr , thresholds = roc_curve(test_y,pred,pos_label = 1)
    auc(fpr,tpr)
    score = accuracy_score(pred,test_y)
    print(score)
#
    predictions = clf.predict(test_df)
#
    return predictions
# --------------------------------------------------------------------------
sys.stderr.write("*** 開始 ***\n")

train_df = read_train_proc()

ids,test_df = read_test_proc()
#
predictions = predict_proc(train_df,test_df)

submit_proc(ids,predictions)

sys.stderr.write("*** 終了 ***\n")
# --------------------------------------------------------------------------

titanic_submit.csv　を　kaggle.com に Submit して次の結果を得ました。

You advanced 11,478 places on the leaderboard!
Your submission scored 0.78468, which is an improvement of your previous score of 0.62200. Great job!