Majority Element Ii
To solve this coding challenge, we need to identify all elements in an integer array that appear more than ⌊n/3⌋ times. The problem demands an O(n) time complexity and O(1) space complexity, making the solution non-trivial. We're utilizing a modified version of the Boyer-Moore Voting Algorithm to achieve this.
times. This involves a few key steps:
Explanation
Here, we try to find elements in the array which appear more thann/3
- Candidate Selection: We first try to identify up to two potential candidates that might be the majority elements. This is because there can be at most 2 elements in an array that appear more than ⌊n/3⌋ times. We use a counter approach for this.
- Validation Phase: After identifying the candidates, we need to verify them by counting their actual occurrences in the array.
- Initialization :
- Create two candidate variables and their associated counts, initializing counts to 0.
- First Pass (Candidate Identification) :
- Iterate through the array.
- Adjust counts based on the current element and update candidates if necessary.
- Second Pass (Validation) :
- Count the occurrences of the identified candidates.
-
Check if they meet the required
threshold.
n/3 -
Initialize variables
,
candidate1to hold potential candidates. Set initial values.candidate2 -
Initialize
and
count1to 0, which will track the count of appearances forcount2andcandidate1, respectively.candidate2 -
Iterate through each number
in the array
num:nums -
If
equals
num, incrementcandidate1.count1 -
Else if
equals
num, incrementcandidate2.count2 -
Else if
is 0, set
count1tocandidate1andnumto 1.count1 -
Else if
is 0, set
count2tocandidate2andnumto 1.count2 -
Otherwise, decrement both
and
count1.count2 - Reset counts to 0 for the second pass:
-
for validating
count1.candidate1 -
for validating
count2.candidate2 -
Iterate through the array again to count the actual occurrences of
and
candidate1.candidate2 -
Check if
or
candidate1occur more thancandidate2times. If they do, add them to the result list.n/3
Step-by-Step Explanation
Detailed Steps in Pseudocode:
Initialization Phase:
# Initialize counters and candidates
count1 = 0
count2 = 0
candidate1 = None
candidate2 = None
First Pass: Candidate Identification
# Iterate through the array to identify potential candidates
for num in nums:
if num == candidate1:
count1 += 1 # Increment count for candidate1
elif num == candidate2:
count2 += 1 # Increment count for candidate2
elif count1 == 0:
candidate1 = num # Set new candidate1
count1 = 1 # Initialize count1
elif count2 == 0:
candidate2 = num # Set new candidate2
count2 = 1 # Initialize count2
else:
count1 -= 1 # Decrement count1
count2 -= 1 # Decrement count2
Second Pass: Validation Phase
# Reset counts for validation
count1 = 0
count2 = 0
# Count occurrences of candidate1 and candidate2 in the array
for num in nums:
if num == candidate1:
count1 += 1 # Increment count for candidate1
elif num == candidate2:
count2 += 1 # Increment count for candidate2
# Prepare the result list
result = []
# Verify if candidates appear more than n/3 times
if count1 > len(nums) / 3:
result.append(candidate1) # Add candidate1 to result
if count2 > len(nums) / 3:
result.append(candidate2) # Add candidate2 to result
# Result contains the majority elements
return result
This approach ensures a time complexity of O(n) and space complexity of O(1). The detailed steps break down how we first select potential candidates and then validate them, ensuring thorough understanding of each phase in this algorithm.