When does pruning stop being efficient in a depth-first search? I've been working on an efficient method to solve the N-Queens problem and I'm looking at pruning for the first time. I've implemented it for the first two rows, but when does it stop being efficient? How far should I prune to?
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Basic question, sorry. Basically, I have a script that creates a MySQL entry each time someone visits the page. A logging script. However, I want to make it autoprune after, say, 100 visits.
For example in pseudo code:
if amount of rows > 100 {
delete rows 1+ until amount of rows == 100 }
So in a nutshell, each time a new row is added...
The MovieLens data set provides a table with columns:
userid | movieid | tag | timestamp
I have trouble reproducing the way they pruned the MovieLens data set used in:
Tag Informed Collaborative Filtering, by Zhen, Li and Young
In 4.1 Data Set of the above paper, it writes
"For the tagging information, we only keep those tags which ...
I currently have a MySQL table of about 20 million rows, and I'm in an urgent need to prune it. I'd like to remove every row whose updateTime (timestamp of insertion) was more than one month ago. I have not personally performed any alterations of the table's order, so the data should be in the order in which it was inserted, and there is...
In alpha, beta pruning algorithm,
I have a class in which a fucntion def getAction(self,gamestate) id defined. I made 2 more function in def getAction
Like:
class BAC:
def you(self,gamestate):
def me(gamestate,depth,alpha, beta):
------
return v
def both(gamestate,depth,alpha, beta):
-------------------
...