Merge pull request #98 from Thomas-George-T/feature_machine_learning

Feature machine learning

README.md

@@ -264,7 +264,51 @@ In managing models for Staging, Production, and Archiving, we rely on MLflow.
    ![Distribution_of_clusters](assets/Distribtion_customers.png)
 
    <p align="center">The plot above visualises the distribution of customers into clusters.</p>
-
+
+# Model Insights
+
+## Segmentation Clusters
+
+### Cluster 0
+
+Profile: Recurrent High Spenders with High Cancellations
+
+- Consumers in this cluster buy a wide range of unusual goods and have very high overall spending power.
+- They do a lot of transactions, but they also cancel a lot and with high frequency.
+- These clients typically shop early in the day and have very short average time intervals between transactions (low Hour value).
+- Their high level of monthly variability suggests that, in comparison to other clusters, their spending patterns may be less predictable.
+- They exhibit a low spending tendency in spite of their high expenditure, which raises the possibility that their high spending levels will eventually decline.
+
+![Cluster 0](data/plots/Cluster0.jpeg)
+
+### Cluster 1
+
+Profile:  Intermittent Big Spenders with a High Spending Trends
+- The moderate spending levels of the customers in this cluster are accompanied by infrequent transactions, as seen by the high Days_Since_Last_Purchase and Average_Days_Between_Purchases values.
+- Their expenditure trend is really high, suggesting that they have been spending more money over time.
+- These clients, who are primarily from the UK, prefer to purchase late in the day, as seen by the high Hour value.
+- They typically cancel a modest amount of transactions, with a moderate frequency and rate of cancellations.
+- Their comparatively high average transaction value indicates that people typically make large purchases when they go shopping.
+
+![Cluster 1](data/plots/Cluster1.jpeg)
+
+### Cluster 2
+
+Profile: Sporadic Shoppers with a Proclivity for Weekend Shopping
+
+- Consumers in this cluster typically make fewer purchases and spend less money overall.
+- The very high Day_of_Week number suggests that they have a slight inclination to shop on the weekends.
+- Their monthly spending variation is low (low Monthly_Spending_Std), and their spending trend is generally constant but on the lower side.
+- These customers have a low cancellation frequency and rate, indicating that they have not engaged in numerous cancellations.
+- When they do shop, they typically spend less each transaction, as seen by the lower average transaction value.
+
+
+![Cluster 1](data/plots/Cluster2.jpeg)
+
+## Customer RFM Trends based on Clusters
+
+![Customer Trends Histogram](data/plots/histogram_analysis.png)
+
 
 <hr> 
 
@@ -390,43 +434,3 @@ Most important declarations in the code:
     ```
 <hr>
 
-# Model Insights
-
-## Segmentation Clusters
-
-### Cluster 0
-Profile: Recurrent High Spenders with High Cancellations
-
-- Consumers in this cluster buy a wide range of unusual goods and have very high overall spending power.
-- They do a lot of transactions, but they also cancel a lot and with high frequency.
-- These clients typically shop early in the day and have very short average time intervals between transactions (low Hour value).
-- Their high level of monthly variability suggests that, in comparison to other clusters, their spending patterns may be less predictable.
-- They exhibit a low spending tendency in spite of their high expenditure, which raises the possibility that their high spending levels will eventually decline.
-
-![Cluster 0](data/plots/Cluster0.jpeg)
-
-### Cluster 1
-Profile:  Intermittent Big Spenders with a High Spending Trends
-- The moderate spending levels of the customers in this cluster are accompanied by infrequent transactions, as seen by the high Days_Since_Last_Purchase and Average_Days_Between_Purchases values.
-- Their expenditure trend is really high, suggesting that they have been spending more money over time.
-- These clients, who are primarily from the UK, prefer to purchase late in the day, as seen by the high Hour value.
-- They typically cancel a modest amount of transactions, with a moderate frequency and rate of cancellations.
-- Their comparatively high average transaction value indicates that people typically make large purchases when they go shopping.
-
-![Cluster 1](data/plots/Cluster1.jpeg)
-
-### Cluster 2
-Profile: Sporadic Shoppers with a Proclivity for Weekend Shopping
-
-- Consumers in this cluster typically make fewer purchases and spend less money overall.
-- The very high Day_of_Week number suggests that they have a slight inclination to shop on the weekends.
-- Their monthly spending variation is low (low Monthly_Spending_Std), and their spending trend is generally constant but on the lower side.
-- These customers have a low cancellation frequency and rate, indicating that they have not engaged in numerous cancellations.
-- When they do shop, they typically spend less each transaction, as seen by the lower average transaction value.
-
-
-![Cluster 1](data/plots/Cluster2.jpeg)
-
-## Customer RFM Trends based on Clusters
-
-![Customer Trends Histogram](data/plots/histogram_analysis.png)