为什么我的逻辑回归模型准确率达到 100%？

Question

Import the libraries

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import sklearn 
from sklearn import preprocessing
import seaborn as sns
%matplotlib inline

Reading the data

 df =pd.read_csv('./EngineeredData_2.csv')
    df =df.dropna()

Split the data into x and y:

X= df.drop (['Week','Div', 'Date', 'HomeTeam', 'AwayTeam','HTHG', 'HTAG','HTR', 
            'FTAG', 'FTHG','HGKPP', 'AGKPP', 'FTR'], axis =1)

Trarnsoforming y into integers:

 L = preprocessing.LabelEncoder ()
    matchresults = L.fit_transform (list (df['FTR']))
    y =list(matchresults)

Split the data into train and test:

from sklearn.model_selection import train_test_split
X_tng,X_tst, y_tng, y_tst =train_test_split (X, y, test_size = 50, shuffle=False)
X_tng.head()

import the class

from sklearn.linear_model import LogisticRegression

Instantiate the model

logreg = LogisticRegression ()

Fit the model with the data

 logreg.fit (X_tng, y_tng)

Predict the test data y_pred = logreg.predict (X_tst)

    acc = logreg. score (X_tst, y_tst)
    print (acc)

Does the accuracy make sense to be 100%?

Answer 1

The problem is that you unintentionally dropped all of your features and only retained your target value in x . So, you are attempting to explain the target value with the target value itself, which of course will give you 100% accuracy. You defined your features columns as:

X= df.drop (['Week','Div', 'Date', 'HomeTeam', 'AwayTeam','HTHG', 'HTAG','HTR', 
            'FTAG', 'FTHG','HGKPP', 'AGKPP', 'FTR'], axis =1)

But you should have defined them as:

X= df.drop('FTR', axis =1)