Add Regression Prediction lab

RegressionPredictionLab/build.gradle

@@ -0,0 +1,32 @@
+import org.springframework.boot.gradle.plugin.SpringBootPlugin
+
+apply plugin: 'java'
+apply plugin: 'org.springframework.boot'
+apply plugin: 'io.spring.dependency-management'
+
+description = "Regression Prediction Lab"
+
+java {
+    sourceCompatibility = JavaVersion.VERSION_21
+    targetCompatibility = JavaVersion.VERSION_21
+}
+
+repositories {
+    mavenCentral()
+}
+
+dependencyManagement {
+    imports {
+        mavenBom SpringBootPlugin.BOM_COORDINATES
+    }
+}
+
+dependencies {
+    implementation 'org.springframework.boot:spring-boot-starter-web'
+
+    implementation 'org.apache.commons:commons-math3:3.6.1'
+    implementation 'com.opencsv:opencsv:5.7.1'
+
+    runtimeOnly 'org.springframework.boot:spring-boot-devtools'
+    testImplementation 'org.springframework.boot:spring-boot-starter-test'
+}

RegressionPredictionLab/src/main/java/com/example/regression/prediction/CustomerPurchasePredictor.java

@@ -0,0 +1,62 @@
+package com.example.regression.prediction;
+
+import org.springframework.boot.autoconfigure.SpringBootApplication;
+import org.apache.commons.math3.stat.regression.SimpleRegression;
+import com.opencsv.CSVReader;
+import com.opencsv.exceptions.CsvException;
+import org.springframework.core.io.ClassPathResource;
+
+import java.io.FileReader;
+import java.io.IOException;
+import java.io.InputStreamReader;
+import java.util.List;
+
+@SpringBootApplication
+public class CustomerPurchasePredictor {
+
+    public static void main(String[] args) {
+        try {
+            // 1. Load the dataset
+            List<String[]> data = loadCSV("/customer_purchases.csv");
+            
+            // 2. Prepare the regression model
+            SimpleRegression regression = new SimpleRegression();
+            
+            // Skip header row and add data points
+            for (int i = 1; i < data.size(); i++) {
+                String[] row = data.get(i);
+                double income = Double.parseDouble(row[2]);  // Independent variable (X)
+                double purchaseAmount = Double.parseDouble(row[3]);  // Dependent variable (Y)
+                regression.addData(income, purchaseAmount);
+            }
+            
+            // 3. Print model statistics
+            System.out.println("=== Model Summary ===");
+            System.out.printf("R-squared: %.4f\n", regression.getRSquare());
+            System.out.printf("Intercept: %.2f\n", regression.getIntercept());
+            System.out.printf("Slope: %.4f\n", regression.getSlope());
+            System.out.printf("Standard Error: %.4f\n\n", regression.getRegressionSumSquares());
+            
+            // 4. Make predictions for new customers
+            System.out.println("=== Predictions ===");
+            predictPurchase(regression, 40000);  // $40,000 income
+            predictPurchase(regression, 55000);  // $55,000 income
+            predictPurchase(regression, 80000);  // $80,000 income
+            
+        } catch (IOException | CsvException e) {
+            e.printStackTrace();
+        }
+    }
+    
+    private static List<String[]> loadCSV(String filePath) throws IOException, CsvException {
+        try (CSVReader reader = new CSVReader(new InputStreamReader(new ClassPathResource(filePath).getInputStream()))) {
+            return reader.readAll();
+        }
+    }
+    
+    private static void predictPurchase(SimpleRegression regression, double income) {
+        double predictedAmount = regression.predict(income);
+        System.out.printf("Predicted purchase for $%,.2f income: $%,.2f\n", 
+                         income, predictedAmount);
+    }
+}

RegressionPredictionLab/src/main/resources/application.properties

@@ -0,0 +1 @@
+spring.application.name=prediction

RegressionPredictionLab/src/main/resources/customer_purchases.csv

@@ -0,0 +1,21 @@
+customer_id,age,income,purchase_amount
+1,25,30000,150
+2,30,35000,180
+3,35,40000,210
+4,40,45000,250
+5,45,50000,280
+6,50,55000,320
+7,55,60000,350
+8,60,65000,380
+9,65,70000,420
+10,70,75000,450
+11,28,32000,160
+12,32,38000,190
+13,38,42000,230
+14,42,48000,260
+15,48,52000,290
+16,52,58000,330
+17,58,62000,360
+18,62,68000,390
+19,68,72000,430
+20,72,78000,460

RegressionPredictionLab/src/test/java/com/example/regression/prediction/PredictionApplicationTests.java

@@ -0,0 +1,13 @@
+package com.example.regression.prediction;
+
+import org.junit.jupiter.api.Test;
+import org.springframework.boot.test.context.SpringBootTest;
+
+@SpringBootTest
+class PredictionApplicationTests {
+
+	@Test
+	void contextLoads() {
+	}
+
+}

settings.gradle

@@ -7,3 +7,4 @@ include 'RetailManagementSystem:front-end'
 include 'InventoryManagementSystem'
 include 'SmartClinicManagementSystem:app'
 include 'SoftwareDevChatbot'
+include 'RegressionPredictionLab'