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Nombre minimum de suppressions pour faire une séquence triée

Essayez-le sur GfG Practice ' title= #practiceLinkDiv { display : aucun !important; }

Étant donné un tableau de n entiers. La tâche consiste à supprimer ou supprimer le nombre minimum d'éléments du tableau de sorte que lorsque les éléments restants sont placés dans le même ordre séquentiel pour former un séquence triée croissante .

Exemples :  

Input : {5 6 1 7 4}  
Output : 2
Removing 1 and 4
leaves the remaining sequence order as
5 6 7 which is a sorted sequence.
Input : {30 40 2 5 1 7 45 50 8}
Output : 4
Recommended Practice Nombre minimum de suppressions pour faire une séquence triée Essayez-le !


UN solution simple est de supprimer toutes les sous-séquences un par un et vérifiez si l'ensemble d'éléments restant est dans l'ordre trié ou non. La complexité temporelle de cette solution est exponentielle.



Un approche efficace utilise le concept de trouver la longueur de la sous-séquence croissante la plus longue d'une séquence donnée.

Algorithme:  

-->    arr    be the given array.  
--> n number of elements in arr .
--> len be the length of longest
increasing subsequence in arr .
-->// minimum number of deletions
min = n - len
C++
// C++ implementation to find  // minimum number of deletions  // to make a sorted sequence #include    using namespace std; /* lis() returns the length  of the longest increasing   subsequence in arr[] of size n */ int lis( int arr[] int n ) {  int result = 0;  int lis[n];  /* Initialize LIS values  for all indexes */  for (int i = 0; i < n; i++ )  lis[i] = 1;  /* Compute optimized LIS   values in bottom up manner */  for (int i = 1; i < n; i++ )  for (int j = 0; j < i; j++ )  if ( arr[i] > arr[j] &&  lis[i] < lis[j] + 1)  lis[i] = lis[j] + 1;  /* Pick resultimum   of all LIS values */  for (int i = 0; i < n; i++ )  if (result < lis[i])  result = lis[i];  return result; } // function to calculate minimum // number of deletions int minimumNumberOfDeletions(int arr[]   int n) {  // Find longest increasing   // subsequence  int len = lis(arr n);  // After removing elements   // other than the lis we   // get sorted sequence.  return (n - len); } // Driver Code int main() {  int arr[] = {30 40 2 5 1  7 45 50 8};  int n = sizeof(arr) / sizeof(arr[0]);  cout << 'Minimum number of deletions = '  << minimumNumberOfDeletions(arr n);  return 0; } 
Java
// Java implementation to find // minimum number of deletions  // to make a sorted sequence class GFG {  /* lis() returns the length   of the longest increasing   subsequence in arr[] of size n */  static int lis( int arr[] int n )  {  int result = 0;  int[] lis = new int[n];    /* Initialize LIS values   for all indexes */  for (int i = 0; i < n; i++ )  lis[i] = 1;    /* Compute optimized LIS   values in bottom up manner */  for (int i = 1; i < n; i++ )  for (int j = 0; j < i; j++ )  if ( arr[i] > arr[j] &&  lis[i] < lis[j] + 1)  lis[i] = lis[j] + 1;    /* Pick resultimum of  all LIS values */  for (int i = 0; i < n; i++ )  if (result < lis[i])  result = lis[i];    return result;  }    // function to calculate minimum  // number of deletions  static int minimumNumberOfDeletions(int arr[]   int n)  {  // Find longest   // increasing subsequence  int len = lis(arr n);    // After removing elements   // other than the lis we get  // sorted sequence.  return (n - len);  }  // Driver Code  public static void main (String[] args)   {  int arr[] = {30 40 2 5 1  7 45 50 8};  int n = arr.length;  System.out.println('Minimum number of' +  ' deletions = ' +  minimumNumberOfDeletions(arr n));  } } /* This code is contributed by Harsh Agarwal */ 
Python3
# Python3 implementation to find  # minimum number of deletions to # make a sorted sequence # lis() returns the length  # of the longest increasing # subsequence in arr[] of size n def lis(arr n): result = 0 lis = [0 for i in range(n)] # Initialize LIS values # for all indexes  for i in range(n): lis[i] = 1 # Compute optimized LIS values  # in bottom up manner  for i in range(1 n): for j in range(i): if ( arr[i] > arr[j] and lis[i] < lis[j] + 1): lis[i] = lis[j] + 1 # Pick resultimum  # of all LIS values  for i in range(n): if (result < lis[i]): result = lis[i] return result # Function to calculate minimum # number of deletions def minimumNumberOfDeletions(arr n): # Find longest increasing  # subsequence len = lis(arr n) # After removing elements  # other than the lis we  # get sorted sequence. return (n - len) # Driver Code arr = [30 40 2 5 1 7 45 50 8] n = len(arr) print('Minimum number of deletions = ' minimumNumberOfDeletions(arr n)) # This code is contributed by Anant Agarwal. 
C#
// C# implementation to find // minimum number of deletions  // to make a sorted sequence using System; class GfG  {    /* lis() returns the length of  the longest increasing subsequence  in arr[] of size n */  static int lis( int []arr int n )  {  int result = 0;  int[] lis = new int[n];    /* Initialize LIS values for  all indexes */  for (int i = 0; i < n; i++ )  lis[i] = 1;    /* Compute optimized LIS values  in bottom up manner */  for (int i = 1; i < n; i++ )  for (int j = 0; j < i; j++ )  if ( arr[i] > arr[j] &&  lis[i] < lis[j] + 1)  lis[i] = lis[j] + 1;    /* Pick resultimum of all LIS  values */  for (int i = 0; i < n; i++ )  if (result < lis[i])  result = lis[i];    return result;  }    // function to calculate minimum  // number of deletions  static int minimumNumberOfDeletions(  int []arr int n)  {    // Find longest increasing  // subsequence  int len = lis(arr n);    // After removing elements other  // than the lis we get sorted  // sequence.  return (n - len);  }  // Driver Code  public static void Main (String[] args)   {  int []arr = {30 40 2 5 1   7 45 50 8};  int n = arr.Length;  Console.Write('Minimum number of' +   ' deletions = ' +   minimumNumberOfDeletions(arr n));  } } // This code is contributed by parashar. 
JavaScript
<script> // javascript implementation to find // minimum number of deletions // to make a sorted sequence /* lis() returns the length of the longest increasing subsequence in arr[] of size n */ function lis(arrn) {  let result = 0;  let lis= new Array(n);  /* Initialize LIS values  for all indexes */  for (let i = 0; i < n; i++ )  lis[i] = 1;  /* Compute optimized LIS  values in bottom up manner */  for (let i = 1; i < n; i++ )  for (let j = 0; j < i; j++ )  if ( arr[i] > arr[j] &&  lis[i] < lis[j] + 1)  lis[i] = lis[j] + 1;  /* Pick resultimum  of all LIS values */  for (let i = 0; i < n; i++ )  if (result < lis[i])  result = lis[i];  return result; } // function to calculate minimum // number of deletions function minimumNumberOfDeletions(arrn) {  // Find longest increasing  // subsequence  let len = lis(arrn);  // After removing elements  // other than the lis we  // get sorted sequence.  return (n - len); }  let arr = [30 40 2 5 17 45 50 8];  let n = arr.length;  document.write('Minimum number of deletions = '  + minimumNumberOfDeletions(arrn)); // This code is contributed by vaibhavrabadiya117. </script> 
PHP
 // PHP implementation to find  // minimum number of deletions  // to make a sorted sequence /* lis() returns the length of   the longest increasing subsequence  in arr[] of size n */ function lis( $arr $n ) { $result = 0; $lis[$n] = 0; /* Initialize LIS values  for all indexes */ for ($i = 0; $i < $n; $i++ ) $lis[$i] = 1; /* Compute optimized LIS   values in bottom up manner */ for ($i = 1; $i < $n; $i++ ) for ($j = 0; $j < $i; $j++ ) if ( $arr[$i] > $arr[$j] && $lis[$i] < $lis[$j] + 1) $lis[$i] = $lis[$j] + 1; /* Pick resultimum of   all LIS values */ for ($i = 0; $i < $n; $i++ ) if ($result < $lis[$i]) $result = $lis[$i]; return $result; } // function to calculate minimum // number of deletions function minimumNumberOfDeletions($arr $n) { // Find longest increasing // subsequence $len = lis($arr $n); // After removing elements  // other than the lis we // get sorted sequence. return ($n - $len); } // Driver Code $arr = array(30 40 2 5 1 7 45 50 8); $n = sizeof($arr) / sizeof($arr[0]); echo 'Minimum number of deletions = '  minimumNumberOfDeletions($arr $n); // This code is contributed by nitin mittal. ?> 

Sortir
Minimum number of deletions = 4

Complexité temporelle : Sur2)
Espace auxiliaire : Sur)

La complexité temporelle peut être réduite à O(nlogn) en trouvant le Taille de sous-séquence croissante la plus longue (N Log N)
Cet article est rédigé par Ayush Jauhari .

Approche n°2 : Utiliser la sous-séquence croissante la plus longue

Une approche pour résoudre ce problème consiste à trouver la longueur de la sous-séquence croissante (LIS) la plus longue du tableau donné et à la soustraire de la longueur du tableau. La différence nous donne le nombre minimum de suppressions requises pour trier le tableau.

Algorithme

1. Calculez la longueur de la sous-séquence croissante (LIS) la plus longue du tableau.
2. Soustrayez la longueur du LIS de la longueur du tableau.
3. Renvoyez la différence obtenue à l’étape 2 comme sortie.

C++
#include    #include  #include    // Required for max_element using namespace std; // Function to find the minimum number of deletions int minDeletions(vector<int> arr) {  int n = arr.size();  vector<int> lis(n 1); // Initialize LIS array with 1    // Calculate LIS values  for (int i = 1; i < n; ++i) {  for (int j = 0; j < i; ++j) {  if (arr[i] > arr[j]) {  lis[i] = max(lis[i] lis[j] + 1); // Update LIS value  }  }  }    // Find the maximum length of LIS  int maxLength = *max_element(lis.begin() lis.end());    // Return the minimum number of deletions  return n - maxLength; } //Driver code int main() {  vector<int> arr = {5 6 1 7 4};    // Call the minDeletions function and print the result  cout << minDeletions(arr) << endl;    return 0; } 
Java
import java.util.Arrays; public class Main {  public static int minDeletions(int[] arr) {  int n = arr.length;  int[] lis = new int[n];  Arrays.fill(lis 1); // Initialize the LIS array with all 1's    for (int i = 1; i < n; i++) {  for (int j = 0; j < i; j++) {  if (arr[i] > arr[j]) {  lis[i] = Math.max(lis[i] lis[j] + 1);  }  }  }    return n - Arrays.stream(lis).max().getAsInt(); // Return the number of elements to delete  }  public static void main(String[] args) {  int[] arr = {5 6 1 7 4};  System.out.println(minDeletions(arr)); // Output: 2  } } 
Python3
def min_deletions(arr): n = len(arr) lis = [1] * n for i in range(1 n): for j in range(i): if arr[i] > arr[j]: lis[i] = max(lis[i] lis[j] + 1) return n - max(lis) arr = [5 6 1 7 4] print(min_deletions(arr)) 
C#
using System; using System.Collections.Generic; using System.Linq; namespace MinDeletionsExample {  class Program  {  static int MinDeletions(List<int> arr)  {  int n = arr.Count;  List<int> lis = Enumerable.Repeat(1 n).ToList(); // Initialize LIS array with 1  // Calculate LIS values  for (int i = 1; i < n; ++i)  {  for (int j = 0; j < i; ++j)  {  if (arr[i] > arr[j])  {  lis[i] = Math.Max(lis[i] lis[j] + 1); // Update LIS value  }  }  }  // Find the maximum length of LIS  int maxLength = lis.Max();  // Return the minimum number of deletions  return n - maxLength;  }  // Driver Code  static void Main(string[] args)  {  List<int> arr = new List<int> { 5 6 1 7 4 };  // Call the MinDeletions function and print the result  Console.WriteLine(MinDeletions(arr));  // Keep console window open until a key is pressed  Console.ReadKey();  }  } } 
JavaScript
function minDeletions(arr) {  let n = arr.length;  let lis = new Array(n).fill(1);  for (let i = 1; i < n; i++) {  for (let j = 0; j < i; j++) {  if (arr[i] > arr[j]) {  lis[i] = Math.max(lis[i] lis[j] + 1);  }  }  }  return n - Math.max(...lis); } let arr = [5 6 1 7 4]; console.log(minDeletions(arr));  

Sortir
2

Complexité temporelle : O(n^2) où n est la longueur du tableau
Complexité spatiale : O(n) où n est la longueur du tableau

Approche n°3 : Utiliser la recherche binaire

Cette approche utilise la recherche binaire pour trouver la position correcte pour insérer un élément donné dans la sous-séquence.

Algorithme

1. Initialisez une liste 'sub' avec le premier élément de la liste d'entrée.
2. Pour chaque élément suivant de la liste d'entrée, s'il est supérieur au dernier élément de « sub », ajoutez-le à « sub ».
3. Sinon, utilisez la recherche binaire pour trouver la position correcte pour insérer l'élément dans 'sub'.
4. Le nombre minimum de suppressions requises est égal à la longueur de la liste d'entrée moins la longueur de « sous ».

C++
#include    #include  using namespace std; // Function to find the minimum number of deletions to make a strictly increasing subsequence int minDeletions(vector<int>& arr) {  int n = arr.size();  vector<int> sub; // Stores the longest increasing subsequence    sub.push_back(arr[0]); // Initialize the subsequence with the first element of the array    for (int i = 1; i < n; i++) {  if (arr[i] > sub.back()) {  // If the current element is greater than the last element of the subsequence  // it can be added to the subsequence to make it longer.  sub.push_back(arr[i]);  } else {  int index = -1; // Initialize index to -1  int val = arr[i]; // Current element value  int l = 0 r = sub.size() - 1; // Initialize left and right pointers for binary search    // Binary search to find the index where the current element can be placed in the subsequence  while (l <= r) {  int mid = (l + r) / 2; // Calculate the middle index    if (sub[mid] >= val) {  index = mid; // Update the index if the middle element is greater or equal to the current element  r = mid - 1; // Move the right pointer to mid - 1  } else {  l = mid + 1; // Move the left pointer to mid + 1  }  }    if (index != -1) {  sub[index] = val; // Replace the element at the found index with the current element  }  }  }  // The minimum number of deletions is equal to the difference between the input array size and the size of the longest increasing subsequence  return n - sub.size(); } int main() {  vector<int> arr = {30 40 2 5 1 7 45 50 8};  int output = minDeletions(arr);  cout << output << endl;    return 0; } 
Java
import java.util.ArrayList; public class Main {  // Function to find the minimum number of deletions to make a strictly increasing subsequence  static int minDeletions(ArrayList<Integer> arr) {  int n = arr.size();  ArrayList<Integer> sub = new ArrayList<>(); // Stores the longest increasing subsequence  sub.add(arr.get(0)); // Initialize the subsequence with the first element of the array  for (int i = 1; i < n; i++) {  if (arr.get(i) > sub.get(sub.size() - 1)) {  // If the current element is greater than the last element of the subsequence  // it can be added to the subsequence to make it longer.  sub.add(arr.get(i));  } else {  int index = -1; // Initialize index to -1  int val = arr.get(i); // Current element value  int l = 0 r = sub.size() - 1; // Initialize left and right pointers for binary search  // Binary search to find the index where the current element can be placed in the subsequence  while (l <= r) {  int mid = (l + r) / 2; // Calculate the middle index  if (sub.get(mid) >= val) {  index = mid; // Update the index if the middle element is greater or equal to the current element  r = mid - 1; // Move the right pointer to mid - 1  } else {  l = mid + 1; // Move the left pointer to mid + 1  }  }  if (index != -1) {  sub.set(index val); // Replace the element at the found index with the current element  }  }  }  // The minimum number of deletions is equal to the difference between the input array size and the size of the longest increasing subsequence  return n - sub.size();  }  public static void main(String[] args) {  ArrayList<Integer> arr = new ArrayList<>();  arr.add(30);  arr.add(40);  arr.add(2);  arr.add(5);  arr.add(1);  arr.add(7);  arr.add(45);  arr.add(50);  arr.add(8);  int output = minDeletions(arr);  System.out.println(output);  } } 
Python3
def min_deletions(arr): def ceil_index(sub val): l r = 0 len(sub)-1 while l <= r: mid = (l + r) // 2 if sub[mid] >= val: r = mid - 1 else: l = mid + 1 return l sub = [arr[0]] for i in range(1 len(arr)): if arr[i] > sub[-1]: sub.append(arr[i]) else: sub[ceil_index(sub arr[i])] = arr[i] return len(arr) - len(sub) arr = [30 40 2 5 1 7 45 50 8] output = min_deletions(arr) print(output) 
C#
using System; using System.Collections.Generic; class Program {  // Function to find the minimum number of deletions to make a strictly increasing subsequence  static int MinDeletions(List<int> arr)  {  int n = arr.Count;  List<int> sub = new List<int>(); // Stores the longest increasing subsequence  sub.Add(arr[0]); // Initialize the subsequence with the first element of the array  for (int i = 1; i < n; i++)  {  if (arr[i] > sub[sub.Count - 1])  {  // If the current element is greater than the last element of the subsequence  // it can be added to the subsequence to make it longer.  sub.Add(arr[i]);  }  else  {  int index = -1; // Initialize index to -1  int val = arr[i]; // Current element value  int l = 0 r = sub.Count - 1; // Initialize left and right   // pointers for binary search  // Binary search to find the index where the current element   // can be placed in the subsequence  while (l <= r)  {  int mid = (l + r) / 2; // Calculate the middle index  if (sub[mid] >= val)  {  index = mid; // Update the index if the middle element is   // greater or equal to the current element  r = mid - 1; // Move the right pointer to mid - 1  }  else  {  l = mid + 1; // Move the left pointer to mid + 1  }  }  if (index != -1)  {  sub[index] = val; // Replace the element at the found index   // with the current element  }  }  }  // The minimum number of deletions is equal to the difference   // between the input list size and the size of the   // longest increasing subsequence  return n - sub.Count;  } // Driver code  static void Main()  {  List<int> arr = new List<int> { 30 40 2 5 1 7 45 50 8 };  int output = MinDeletions(arr);  Console.WriteLine(output);  Console.ReadLine();  } } 
JavaScript
// Function to find the minimum number of deletions to make a strictly increasing subsequence function minDeletions(arr) {  let n = arr.length;  let sub = []; // Stores the longest increasing subsequence  sub.push(arr[0]); // Initialize the subsequence with the first element of the array  for (let i = 1; i < n; i++) {  if (arr[i] > sub[sub.length - 1]) {  // If the current element is greater than the last element of the subsequence  // it can be added to the subsequence to make it longer.  sub.push(arr[i]);  } else {  let index = -1; // Initialize index to -1  let val = arr[i]; // Current element value  let l = 0 r = sub.length - 1; // Initialize left and right pointers for binary search  // Binary search to find the index where the current element can be placed   // in the subsequence  while (l <= r) {  let mid = Math.floor((l + r) / 2); // Calculate the middle index  if (sub[mid] >= val) {  index = mid; // Update the index if the middle element is greater   //or equal to the current element  r = mid - 1; // Move the right pointer to mid - 1  } else {  l = mid + 1; // Move the left pointer to mid + 1  }  }  if (index !== -1) {  sub[index] = val; // Replace the element at the found index with the current element  }  }  }  // The minimum number of deletions is equal to the difference  //between the input array size and the size of the longest increasing subsequence  return n - sub.length; } let arr = [30 40 2 5 1 7 45 50 8]; let output = minDeletions(arr); console.log(output); 

Sortir
4

Complexité temporelle : O (n log n)

Espace auxiliaire : O(n)

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