levenshtein-distance-algo

Algorithms_and_Data_Structures/Dynamic-Programming-Series/Hard-DP-Problems/levenshtein-distance.py

@@ -0,0 +1,27 @@
+def minDistance(word1, word2):
+    m, n = len(word1), len(word2)
+
+    # Initialize a (m+1) x (n+1) dp table
+    dp = [[0] * (n + 1) for _ in range(m + 1)]
+
+    for i in range(m + 1):
+        dp[i][0] = i 
+    for j in range(n + 1):
+        dp[0][j] = j  
+
+    for i in range(1, m + 1):
+        for j in range(1, n + 1):
+            if word1[i - 1] == word2[j - 1]:
+                dp[i][j] = dp[i - 1][j - 1] 
+            else:
+                dp[i][j] = min(
+                    dp[i - 1][j] + 1,      
+                    dp[i][j - 1] + 1,      
+                    dp[i - 1][j - 1] + 1 
+                )
+
+    return dp[m][n]
+
+word1 = "horse"
+word2 = "ros"
+print(f"Minimum edit distance to convert '{word1}' to '{word2}': {minDistance(word1, word2)}")