[Question] What is the default value of K (Max Conflict Count)?

[deana00]

Hello, I have few questions regarding the algorithm of LightGBM. Currently, I am using LightGBM for my undergraduate thesis.

1. In the Greedy Bundling algorithm showed above as in the LightGBM paper (https://proceedings.neurips.cc/paper_files/paper/2017/file/6449f44a102fde848669bdd9eb6b76fa-Paper.pdf), what is the default value of K (max conflict count)? Do we need to assign it explicitly? Can you please show me the code where K is used?
2. For binary classification, how to calculate gain? Can you please give me an example of the calculations?
3. If I have features
   F0 = [1,0,1,0,2,3,0,1,1,2] and
   F1 = [0,1,0,3,0,0,0,4,0,0],
   which one is correct between newBundle = [4,8,4,10,5,6,0,11,4,5] as Algorithm 4 in the paper,
   newBundle = [1,4,1,6,2,3,0,7,1,2], or newBundle = [1,4,1,6,2,3,0,1,1,2]?
4. In Algorithm 4 below, where does the value of numBin come from? How do we know the value of numBin for each features?
   
5. How do we get the value of bin boundaries?

I am sorry for asking too much questions. But I hope someone here can give me better understanding, thank you.

Edited:

1. Already answered here Exclusive Feature Bundle is for categorical data only? #4114 (comment). Default value of K is number of data/10000, no?

[shiyu1994]

@deana00 Link to the value of K here.

LightGBM/src/io/dataset.cpp

Line 115 in fe7f8fe

const data_size_t single_val_max_conflict_cnt =

It is about 1/10000 of the number of sampled data used to determine the groups and bins.

[deana00]

@deana00 Link to the value of K here.

LightGBM/src/io/dataset.cpp

Line 115 in fe7f8fe

const data_size_t single_val_max_conflict_cnt =

It is about 1/10000 of the number of sampled data used to determine the groups and bins.

Hi, thank you for your response. Can you elaborate your last sentence about determining the bins?

So, how do we determine the number of bin and the bin boundaries needed to build histogram?