What is the difference between time complexity and sample complexity?

1. What do you mean by sample complexity?
2. What is the difference between time complexity and computational complexity?
3. What is the difference between time complexity?
4. What is the meaning of time complexity O N?

What do you mean by sample complexity?

The sample complexity of a machine learning algorithm represents the number of training-samples that it needs in order to successfully learn a target function.

What is the difference between time complexity and computational complexity?

Computational complexity may refer to any of the cost models; time complexity usually just refers to the time-based ones—for example, the time complexity of heap sort is O(nlogn) while the space complexity is O(n), assuming memory access cost is constant, yet in the more realistic AT metric the best-known cost of ...

What is the difference between time complexity?

Time complexity is a complete theoretical concept related to algorithms, while running time is the time a code would take to run, not at all theoretical. Two algorithms may have the same time complexity, say O(n^2), but one may take twice as much running time as the other one.

What is the meaning of time complexity O N?

Linear time complexity O(n) means that the algorithms take proportionally longer to complete as the input grows. Examples of linear time algorithms: Get the max/min value in an array. Find a given element in a collection.