Answer:
Greedy is an algorithmic paradigm that builds up a solution piece by piece, always choosing the next piece that offers the most obvious and immediate benefit. Greedy algorithms are used for optimization problems. An optimization problem can be solved using Greedy if the problem has the following property: At every step, we can make a choice that looks best at the moment, and we get the optimal solution of the complete problem.
If a Greedy Algorithm can solve a problem, then it generally becomes the best method to solve that problem as the Greedy algorithms are in general more efficient than other techniques like Dynamic Programming. But Greedy algorithms cannot always be applied. For example, the Fractional Knapsack problem (See this) can be solved using Greedy, but 0-1 Knapsack cannot be solved using Greedy.
The following are some standard algorithms that are Greedy algorithms.
1) Kruskal’s Minimum Spanning Tree (MST): In Kruskal’s algorithm, we create an MST by picking edges one by one. The Greedy Choice is to pick the smallest weight edge that doesn’t cause a cycle in the MST constructed so far.
2) Prim’s Minimum Spanning Tree: In Prim’s algorithm also, we create an MST by picking edges one by one. We maintain two sets: a set of the vertices already included in MST and the set of the vertices not yet included. The Greedy Choice is to pick the smallest weight edge that connects the two sets.
3) Dijkstra’s Shortest Path: Dijkstra’s algorithm is very similar to Prim’s algorithm. The shortest-path tree is built up, edge by edge. We maintain two sets: a set of the vertices already included in the tree and the set of the vertices not yet included. The Greedy Choice is to pick the edge that connects the two sets and is on the smallest weight path from source to the set that contains not yet included vertices.
4) Huffman Coding: Huffman Coding is a loss-less compression technique. It assigns variable-length bit codes to different characters. The Greedy Choice is to assign the least bit length code to the most frequent character. The greedy algorithms are sometimes also used to get an approximation for Hard optimization problems. For example, the Traveling Salesman Problem is an NP-Hard problem. A Greedy choice for this problem is to pick the nearest unvisited city from the current city at every step. These solutions don’t always produce the best optimal solution but can be used to get an approximately optimal solution.
After the initial rollout of the new network generation, the new network generation will be Created and boasted in all of its lifelines.
<h3>What happens after rollout of a new
network generation?</h3>
After the initial passage of the new network generation, the new network generation will be created and worked on well in all of its lifetime.
This is because due to the creation of new network generation, new networks will be consistently updated and created to get a lot of or maximum results.
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Answer:
External Data is the correct answer.
Explanation:
In the following statement, if the user wants to transfer data from query to Excel then, they follow these steps.
- Firstly, they have to click on the Tools.
- Then, they click on the options.
- Then, they have to click on the Query then, click on the external data on the ribbon.
- Finally, they click on the Excel button.
Select OLAP tools in the Tools group under the Options tab, and then click Convert to Formulas. The conversion process is finished if there are no report filters. Convert to Formulas dialog box appears if there are one or more report filters. Thus, option D is correct.
<h3>What role of the GETPIVOTDATA function in
pivot table?</h3>
You can extract data from a pivot table using Sheets' GETPIVOTDATA function. You must first create a pivot table before using it.
Then, you use the GETPIVOTDATA function and supply the column name and row number of the data you wish to extract in order to extract it from the table.
Therefore, The GETPIVOTDATA function returns visible data from a Pivot Table.
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Answer:
Enter USD and select desired currency.
US Dollars (USD): 100.00
Select Currency: Canadian Dollar (CAN)
Canadian Dollar (CAN): 130.00
Explanation:
See full code attached.