DEVELOPMENT... OpenML
Data
Arcade-Game-Stats

Arcade-Game-Stats

active ARFF CC0: Public Domain Visibility: public Uploaded 23-03-2022 by Lowe
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
Statistics on a Blockbreaker-like Game The author is in the process of creating a blockbreaker-like game, in which the jumping-off point is the "Block Breaker" section of the Udemy course, Complete C Unity Developer 2D: Learn to Code Making Games After making lots of levels, the author needed to sort them by difficulty. How does one measure the difficulty of a level? A first-cut solution is to make an auto-play bot that is not perfect, and see how well the bot does on each level, using thousands of trials. Here is a video of the game in auto-play action. Fields Date: date and time the game was auto-played Level: the name of the level (the 3-digit number is an estimate of the difficulty from a previous run, no longer valid after tweaking) NumBlocks: how many blocks have to be broken to win the level IsWin: True if autoplay broke all the blocks, False if the ball fell past the paddle. ElapsedTime: Seconds until either won or lost (game is played at 4x speed, so multiply by 4 to get an estimate of how long a human might play it) Score: total score when the game was won or lost Accuracy: the autoplay is tuned with a randomly-chosen accuracy. Higher numbers are more likely to win.

7 features

Datestring6770 unique values
0 missing
Levelstring19 unique values
0 missing
NumBlocksnumeric18 unique values
0 missing
IsWinnominal2 unique values
0 missing
ElapsedTimenumeric6789 unique values
0 missing
Scorenumeric176 unique values
0 missing
Accuracynumeric6778 unique values
0 missing

19 properties

6814
Number of instances (rows) of the dataset.
7
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
4
Number of numeric attributes.
1
Number of nominal attributes.
14.29
Percentage of nominal attributes.
Average class difference between consecutive instances.
57.14
Percentage of numeric attributes.
0
Percentage of missing values.
0
Percentage of instances having missing values.
14.29
Percentage of binary attributes.
1
Number of binary attributes.
Number of instances belonging to the least frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the most frequent class.
0
Number of attributes divided by the number of instances.

0 tasks

Define a new task