I have built the model on Titanic Data set , with Logistic Regression Succeffullly and it is giving prediction on training set , but unfortunately I am unable to implement this on test data set.
Following code for reference :
training = training[['PassengerId','Sex','Embarked','Pclass','Age','SibSp','Survived']] # 0.78 X = training.iloc[:, :-1] y = training.iloc[:, -1] from sklearn.compose import make_column_transformer from sklearn.preprocessing import OneHotEncoder ct = make_column_transformer((OneHotEncoder(), ['Sex', 'Embarked']), remainder = 'passthrough') X = ct.fit_transform(X) from sklearn.preprocessing import StandardScaler sc =StandardScaler() X=sc.fit_transform(X) from sklearn.linear_model import LogisticRegression logreg = LogisticRegression(solver = 'lbfgs') from sklearn.model_selection import cross_val_score cross_val_score(logreg, X,y, cv=5, scoring ='accuracy').mean()
As in the test data set , I don't have y data that means the predictive column so I introduced it with the help of null values.
But unable to take it forward, Can you please guide , how I can run Logistic Regression Model on test data set of Titanic.
Thanks a lot .