@ Dave. Nice explanation

On Fri, May 20, 2011 at 6:06 AM, saurabh agrawal <saurabh...@gmail.com>wrote:

> Thanks Dave.
>
> On Wed, May 18, 2011 at 8:01 PM, Dave <dave_and_da...@juno.com> wrote:
>
>> @Saurabh: You look at the top elements in the two heaps. If the new
>> number is between the values of the top of the heaps, you add it to
>> the shorter of the two heaps, or to either heap if they are of equal
>> length. If the new number is larger than the min of the min-heap, you
>> add it to the min-heap. If it is smaller than the max of the max-heap,
>> you add it to the max heap. If the resulting two heaps differ in
>> length by more than one element, you move the top element from the
>> longer heap into the shorter heap. Since the heaps start off empty and
>> you add only one number at a time, the result of a step of the
>> algorithm is that the two heaps will differ in size by at most one
>> element. Thus, the smaller half of the numbers will be in the max-heap
>> and the larger half will be in the min-heap.
>>
>> Dave
>>
>> On May 18, 8:29 am, saurabh agrawal <saurabh...@gmail.com> wrote:
>> > Dave,
>> > u said:" a max-heap of the smallest
>> > half of the elements"
>> > but if the number are randomply generated, then how will you get to know
>> > whether a number belongs to smallest half OR lager half..
>> > i didnt got it...
>> >
>> >
>> >
>> > On Sat, May 14, 2011 at 9:10 PM, Dave <dave_and_da...@juno.com> wrote:
>> > > @Ashish: The idea is to keep two heaps, a max-heap of the smallest
>> > > half of the elements and a min-heap of the largest elements. You
>> > > insert incoming elements into the appropriate heap. If the result is
>> > > that the number of elements in the two heaps differs by more than 1,
>> > > then you move the top element from the longer heap into the other one,
>> > > thereby equalzing the number of elements. Thus, inserting an element
>> > > is an O(log n) operation. To get the median, it is the top element of
>> > > the longer heap, or, if the heaps are of equal length, it is the
>> > > average of the two top elements. This is O(1).
>> >
>> > > Dave
>> >
>> > > On May 14, 8:34 am, Ashish Goel <ashg...@gmail.com> wrote:
>> > > > not clear, can u elaborate..
>> >
>> > > > Best Regards
>> > > > Ashish Goel
>> > > > "Think positive and find fuel in failure"
>> > > > +919985813081
>> > > > +919966006652
>> >
>> > > > On Fri, May 13, 2011 at 7:15 PM, Bhavesh agrawal <
>> agr.bhav...@gmail.com
>> > > >wrote:
>> >
>> > > > > This problem can be solved using 2 heaps and the median can always
>> be
>> > > > > accessed in O(1) time ,the first node.
>> >
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