1. Use the binScramble.cpp to scramble data before clustering
Example:
g++ binScramblefloat.cpp memAllocation.cpp -o binScramblefloat
Usage:binscramblefloat infile.bin(input data) scrambledfile.bin(output file) size(no. of examples) s(features)
Example: binscramblefloat iris.bin siris.bin 150 4

2. Use the singlePass.cpp to cluster the scrambled data.
Example:
g++ singlePass.cpp memAllocation.cpp -O3 -o singlePass
Usage: singlePass iris.bin(binary form) percent(how much % data to be loaded each time) 
Example: singlePass iris.bin 10
Please Note: The algorithm assumes data is reasonably scrambled. If not, scramble it by using the
binScramblefloat.cpp program. This program will take any data set (float binary format) and output
a scrambled data set.  
