In linear search, the searched key will be compared with each element of the array from the beginning and terminate comparing when the searched key is found or the array is reached. Here time complexity in worst case and average case is O (n).
To find an element quickly we use divide and conquer method by using binary search algorithm. Here probed region is reduced from n to n/2. Time complexity is O (log2 n), but here the array should be sorted.
But in interpolation search the probed region is reduced from n to n1/2. If the array elements are uniformly distributed the average case complexity is O (log2 (log2n)).
Am also searching for hashing to compare & contrast with above.
Binary search is faster than linear search, particularly when searching large sets of data. However, binary search only works when the data is ordered (sorted). If the data is unordered (unsorted), you must use a linear search.
Binary search works by selecting the middle element of a set. Knowing that the set is ordered means that if the middle item is not the value your looking for, comparing both values will tell you which half of the set holds the value, which means you can eliminate the other half completely. You then repeat the process with the remaining half. Eventually you will either locate the value or the remaining half will be empty, in which case the value does not exist. Thus for a set of 100 elements, we would need no more than 7 comparisons in total to determine that a value does not exist in the set. With linear search, we would need to perform 100 comparisons every time. If the value does exist in the set, the average number of comparisons for binary search is 2 but for linear search it is 50. The best case is 1 comparison for both, but that only happens when the value we seek is the first value we check, which would only happen about 1 in every 100 searches on average.
in liner search the array is not mandatory to be a sorted array,but in binary search the array must be a sorted array.
When binary search is not possible. For example: unsorted data, data with variable length, only sequentially accessible data (tape).
If the data is unsorted, or the records' size are variable, or only sequential access is possible, then linear search is much better than binary search. (Because the latter is unusable.)
(i) Binary search can interact poorly with the memory hierarchy (i.e. caching), because of its random-access nature. For in-memory searching, if the interval to be searching is small, a linear search may have superior performance simply because it exhibits better locality of reference. (ii) Binary search algorithm employs recursive approach and this approach requires more stack space. (iii) Programming binary search algorithm is very difficult and error prone (Kruse, 1999).
A tree doesn't do anything so it has no speed...
There are two types of searching technique used in data structure.such as linear and binary search.
The best search programs to attempt writing in C are the following: Linear search (simplest), Binary search (faster) Hash search (fastest).
Linear search takes linear time with a worst case of O(n) for n items, and an average of O(n/2). Binary search takes logarithmic time, with a worst and average case of O(n log n). Binary search is therefore faster on average.
4 more info search how dangerous is the swine flu
(i) Binary search can interact poorly with the memory hierarchy (i.e. caching), because of its random-access nature. For in-memory searching, if the interval to be searching is small, a linear search may have superior performance simply because it exhibits better locality of reference. (ii) Binary search algorithm employs recursive approach and this approach requires more stack space. (iii) Programming binary search algorithm is very difficult and error prone (Kruse, 1999).
In the worst case a binary search tree is linear and has a height equal to the number of nodes. so h=O(h).
A tree doesn't do anything so it has no speed...
There are two types of searching technique used in data structure.such as linear and binary search.
The best search programs to attempt writing in C are the following: Linear search (simplest), Binary search (faster) Hash search (fastest).
Linear search, also known as sequential search, is a process that checks every element in the list sequentially until the desired element is found. The computational complexity for linear search is O(n), making it generally much less efficient than binary search (O(log n)). But when list items can be arranged in order from greatest to least and the probabilities appear as geometric distribution (f (x)=(1-p) x-1p, x=1,2),then linear search can have the potential to be notably faster than binary search.
It's called "Linear Search". If the list is sorted, then it is possible to perform more advanced searches like binary search. If the list isn't sorted, then you can either sort the list first and then binary search or simply use a linear search. Linear search is typically a brute force solution when the data isn't "planned" or if the data is stored in a linked list where random access of the values in the list is slow.
Linear search takes linear time with a worst case of O(n) for n items, and an average of O(n/2). Binary search takes logarithmic time, with a worst and average case of O(n log n). Binary search is therefore faster on average.
If the data is sorted and every element is directly accessible, then you can perform binary search (see built-in function bsearch), otherwise you have to do linear search (which is slower).
You can check out the Arrays.binarySearch group of methods for searching sorted arrays. There is no predefined linear search for arrays, probably because it is trivially easy to implement. If you have some other data structure to search, the Collections.binarySearch methods should work for you. Most collections can also be converted to a List representation, which has a predefined indexOf method for linear searching.
________________________________________________________________________________| Binary search | Linear search |-------------------------------------------------------------------------------------------------------------------------1).Data must be in a sorted order | 1).Data any order2).Time complexity is O(log n) | 2).Time complexity is O(n).3).Only 1 "When" condition used | 3).Any no. of "When" condition used4).Only "=" relation operator is used | 4).any relation operator is used5).Access is faster | 5).Access is slow6).Only single dimensional array used | 6).single/multi dimensional array usedA linear search works by looking at each element in a list of data until it either finds the target or reaches the end. This results in O(n) performance on a given list.A binary search comes with the prerequisite that the data must be sorted. We can leverage this information to decrease the number of items we need to look at to find our target. We know that if we look at a random item in the data (let's say the middle item) and that item is greater than our target, then all items to the right of that item will also be greater than our target. This means that we only need to look at the left part of the data. Basically, each time we search for the target and miss, we can eliminate half of the remaining items. This gives us a nice O(log n) time complexity.Just remember that sorting data, even with the most efficient algorithm, will always be slower than a linear search (the fastest sorting algorithms are O(n * log n)). So you should never sort data just to perform a single binary search later on. But if you will be performing many searches (say at least O(log n) searches), it may be worthwhile to sort the data so that you can perform binary searches. You might also consider other data structures such as a hash table in such situations.binary search runs in O(logn) time whereas linear search runs in O(n) times thus binary search has better performance.