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ML's yellowbrick: A case of interpretability (threshold map) for LoR logistic regression model using yellowbrick based on whether Titanic was rescued or not based on the two-class prediction dataset

2022-08-03 22:45:00 【A virgo's program ape】

ML之yellowbrick：基于titanic泰坦尼克是否获救二分类预测数据集利用yellowbrick对LoRLogistic regression models enable interpretability(阈值图)案例

基于titanic泰坦尼克是否获救二分类预测数据集利用yellowbrick对LoRLogistic regression models enable interpretability(阈值图)案例

# 2.3、特征之间Pearson相关性可视化

# 3、模型建立

# 4、Model Interpretability Visualization

# 4.1、阈值图：基于yellowbrickThe library enables model interpretability

基于titanic泰坦尼克是否获救二分类预测数据集利用yellowbrick对LoRLogistic regression models enable interpretability(阈值图)案例

# 1、定义数据集

PassengerId	Survived	Pclass	Name	Sex	Age	SibSp	Parch	Ticket	Fare	Cabin	Embarked
1	0	3	Braund, Mr. Owen Harris	male	22	1	0	A/5 21171	7.25		S
2	1	1	Cumings, Mrs. John Bradley (Florence Briggs Thayer)	female	38	1	0	PC 17599	71.2833	C85	C
3	1	3	Heikkinen, Miss. Laina	female	26	0	0	STON/O2. 3101282	7.925		S
4	1	1	Futrelle, Mrs. Jacques Heath (Lily May Peel)	female	35	1	0	113803	53.1	C123	S
5	0	3	Allen, Mr. William Henry	male	35	0	0	373450	8.05		S

# 2、数据预处理

# 2.1、类别特征编码

# 2.2、特征筛选且空值填充

Pclass Age SibSp Parch Fare Sex_encoding Embarked_encoding \
0 3 22.0 1 0 7.2500 1 0
1 1 38.0 1 0 71.2833 0 1
2 3 26.0 0 0 7.9250 0 0
3 1 35.0 1 0 53.1000 0 0
4 3 35.0 0 0 8.0500 1 0

Survived
0 0
1 1
2 1
3 1
4 0