From 2bca96a0f6416da6c13b5ebf2ce9be83ecc29abb Mon Sep 17 00:00:00 2001 From: Pritimay Sarkar Date: Sun, 1 Oct 2023 15:10:18 +0530 Subject: [PATCH] add cm plot --- scripts/logistic.py | 14 +++++++++++++- 1 file changed, 13 insertions(+), 1 deletion(-) diff --git a/scripts/logistic.py b/scripts/logistic.py index 54f4747..cbd97b1 100644 --- a/scripts/logistic.py +++ b/scripts/logistic.py @@ -2,7 +2,7 @@ import pandas as pd from sklearn.model_selection import train_test_split from sklearn.linear_model import LogisticRegression from sklearn.preprocessing import LabelEncoder -from sklearn.metrics import accuracy_score, classification_report +from sklearn.metrics import accuracy_score, classification_report, confusion_matrix import pickle import statsmodels.api as sm import matplotlib.pyplot as plt @@ -38,6 +38,18 @@ accuracy = accuracy_score(y_test, y_pred) classification_report_result = classification_report(y_test, y_pred) #sns.heatmap(pd.DataFrame(classification_report_result).iloc[:-1, :].T, annot=True) + +# Calculate the confusion matrix +confusion = confusion_matrix(y_test, y_pred) + +# Plot the confusion matrix using Seaborn +plt.figure(figsize=(8, 6)) +sns.heatmap(confusion, annot=True, fmt='d', cmap='Blues', linewidths=0.5) +plt.xlabel('Predicted') +plt.ylabel('Actual') +plt.title('Confusion Matrix') +plt.show() + print(f"Accuracy: {accuracy}") print("Classification Report:") print(classification_report_result)