Update README.md

Health Insurance Cross Sell Prediction/images/README.md

@@ -4,34 +4,44 @@ This folder contains various visualizations that represent different aspects of
 ## Visualizations
 - **Correlation Matrix:**
 This matrix shows the correlation between different features in the dataset, providing insight into how variables are related to each other.
+<img width="566" alt="correlation" src="https://github.com/user-attachments/assets/aee01c65-aa02-4dd2-9c77-eb5451df1dc8">
 
 
 - **Distribution of Response:**
 This chart displays the distribution of the target variable Response. It shows the frequency of positive and negative responses in the dataset.
+<img width="397" alt="distribution_response" src="https://github.com/user-attachments/assets/1dbf1549-6a83-4bcb-b285-eb5499df880f">
 
 - **Distribution Based on Gender:**
 Description: This chart shows the distribution of the Gender variable, illustrating the proportion of male and female customers.
+<img width="404" alt="gender_response" src="https://github.com/user-attachments/assets/ca61e4c1-3430-4594-82e8-abb56285fea4">
 
 - **Gender Distribution:**
 Description: This visualization represents the count of responses from different genders, helping to understand the gender demographics of the dataset.
+<img width="230" alt="gender" src="https://github.com/user-attachments/assets/4dc42fba-9bd3-47b0-a49e-ef938858b447">
 
 - **Distribution of Age:**
 Description: This chart displays the distribution of the Age variable, showing the age range and frequency of customers in the dataset.
+<img width="518" alt="dis_age" src="https://github.com/user-attachments/assets/6bbb4aff-436b-4b43-a2c8-db16b176fe2c">
 
 - **Histograms of Selected Columns:**
 Description: These histograms show the distribution of values for selected columns such as Annual_Premium, Policy_Sales_Channel, and Vintage. They provide insight into the data distribution for these features.
+<img width="775" alt="histogram" src="https://github.com/user-attachments/assets/851989ee-bcaa-4ab6-88d0-2f87c56a961f">
 
 - **F1 Score Comparison:**
 Description: This bar chart compares the F1 scores of different models used in the analysis. The F1 score is a measure of a model's accuracy, balancing precision and recall.
+<img width="587" alt="f1_cmp" src="https://github.com/user-attachments/assets/51c4ddf5-e032-4cbc-af2d-66cfda1be209">
 
 - **Recall Comparison:**
 Description: This bar chart compares the recall scores of different models used in the analysis. Recall measures the ability of a model to identify all relevant instances in the dataset.
+<img width="572" alt="recall_cmp" src="https://github.com/user-attachments/assets/a4329cb8-f658-42d3-8dd6-952b52535656">
 
 - **Precision Comparison:**
 Description: This bar chart compares the precision scores of different models used in the analysis. Precision measures the accuracy of the positive predictions made by the model.
+<img width="584" alt="precision_cmp" src="https://github.com/user-attachments/assets/4bb39a4c-1aec-4f12-9319-a67e481e111c">
 
 - **Accuracy Comparison:**
 Description: This bar chart compares the accuracy scores of different models used in the analysis. Accuracy measures the overall correctness of the model's predictions.
+<img width="482" alt="model_cmp" src="https://github.com/user-attachments/assets/c63dd77d-0e85-4acb-a847-df8aa6e20fe0">
 
 ### Usage
-These visualizations provide a comprehensive view of the dataset's characteristics and the performance of various models used for sentiment analysis. They can be used to gain insights into customer demographics, feature distributions, and model effectiveness, aiding in identifying areas for improvement in the analysis.
+These visualizations provide a comprehensive view of the dataset's characteristics and the performance of various models used for sentiment analysis. They can be used to gain insights into customer demographics, feature distributions, and model effectiveness, aiding in identifying areas for improvement in the analysis.