#practiceLinkDiv { display: none !important; }Gegeben sei ein Array mit n ganzen Zahlen. Die Aufgabe besteht darin, die Mindestanzahl an Elementen aus dem Array zu entfernen oder zu löschen, sodass, wenn die verbleibenden Elemente in derselben Reihenfolge platziert werden, ein Array entsteht zunehmende sortierte Reihenfolge .
Beispiele:
Input : {5 6 1 7 4}Recommended Practice Mindestanzahl an Löschvorgängen, um eine sortierte Sequenz zu erstellen Probieren Sie es aus!
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
A einfache Lösung ist zu entfernen alle Teilfolgen nacheinander und prüfen Sie, ob der verbleibende Satz von Elementen in sortierter Reihenfolge ist oder nicht. Die zeitliche Komplexität dieser Lösung ist exponentiell.
Ein effizienter Ansatz verwendet das Konzept von Ermitteln der Länge der am längsten ansteigenden Teilfolge einer gegebenen Sequenz.
Algorithmus:
kein Eingangssignal
--> arr be the given array.C++
--> n number of elements in arr .
--> len be the length of longest
increasing subsequence in arr .
-->// minimum number of deletions
min = n - len
// 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. ?> Ausgabe
Minimum number of deletions = 4
Zeitkomplexität: An2)
Hilfsraum: An)
Die Zeitkomplexität kann auf O(nlogn) verringert werden, indem die ermittelt wird Längste ansteigende Teilsequenzgröße (N Log N)
Dieser Artikel wurde verfasst von Ayush Jauhari .
Ansatz Nr. 2: Verwendung der am längsten ansteigenden Teilsequenz
Ein Ansatz zur Lösung dieses Problems besteht darin, die Länge der längsten ansteigenden Teilsequenz (LIS) des gegebenen Arrays zu ermitteln und diese von der Länge des Arrays zu subtrahieren. Die Differenz gibt uns die Mindestanzahl an Löschungen an, die erforderlich sind, um das Array zu sortieren.
Algorithmus
1. Berechnen Sie die Länge der längsten ansteigenden Teilsequenz (LIS) des Arrays.
2. Subtrahieren Sie die Länge des LIS von der Länge des Arrays.
3. Geben Sie die in Schritt 2 erhaltene Differenz als Ausgabe zurück.
#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));
Ausgabe
2
Zeitkomplexität: O(n^2), wobei n die Länge des Arrays ist
Raumkomplexität: O(n), wobei n die Länge des Arrays ist
Ansatz Nr. 3: Verwendung der binären Suche
Dieser Ansatz verwendet die binäre Suche, um die richtige Position zum Einfügen eines bestimmten Elements in die Teilsequenz zu finden.
Algorithmus
1. Initialisieren Sie eine Liste „sub“ mit dem ersten Element der Eingabeliste.
2. Hängen Sie jedes nachfolgende Element in der Eingabeliste, wenn es größer als das letzte Element in „sub“ ist, an „sub“ an.
3. Andernfalls verwenden Sie die binäre Suche, um die richtige Position zum Einfügen des Elements in „sub“ zu finden.
4. Die erforderliche Mindestanzahl an Löschvorgängen entspricht der Länge der Eingabeliste minus der Länge von „sub“.
#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);
Ausgabe
4
Zeitkomplexität: O(n log n)
Hilfsraum: O(n)
Quiz erstellen