question stringlengths 1k 17.3k | answer stringlengths 9 5.47k |
|---|---|
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
3 2 3 2 3 2
7 8 7 8 7 8
2 3 2 3 2 3
8 7 8 7 8 7
3 2 3 2 3 2
7 8 7 8 7 8
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
7 0 7 0 0 0 7 0 7
7 0 7 0 0 0 7 0 7
7 7 0 0 0 0 7 7 0
7 0 7 0 0 0 7 0 7
7 0 7 0 0 0 7 0 7
7 7 0 0 0 0 7 7 0
7 0 7 7 0 7 0 0 0
7 0 7 7 0 7 0 0 0
7 7 0 7 7 0 0 0 0
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 7 7 7 7 7 7 7 7 7
0 0 0 0 0 7 0 0 0 7 0 7 0 7
0 0 0 0 0 7 0 7 0 7 0 0 0 7
0 0 0 0 0 7 7 7 7 7 7 7 7 7
0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 ... |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 3 4 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 3 0 3 3 3 3 3 0 3 3 0 0 0 0 0 0 0 0
0 0 0 0 3 4 4 4 4 3 4 4 3 0 0 0 0 0 0 0
0 0 0 0 3 3 3 3 3 0 3 3 3 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 3 3 3 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 3 4 4 4 3 ... |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 0 0 0 0 0 2 2 2 2 2 0 0 0 0
0 2 2 2 2 2 2 2 2 2 0 2 8 8 8 2 0 0 0 0
0 2 3 3 3 3 3 3 3 2 0 2 8 2 8 2 0 0 0 0
0 2 3 3 3 3 3 3 3 2 0 2 8 8 8 2 0 0 0 0
0 2 3 3 3 3 3 3 3 2 0 2 2 2 2 2 0 0 0 0
0 2 3 3 3 2 3 3 3 2 0 0 0 0 0 0 0 0 0 0
0 2 3 3 3 3 3 3 3 2 0 0 0 0 0 0 0 0 0 0
0 2 3 3 3 3 3 3 3 2 0 0 0 2 2 2 2 2 ... |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
2 2 2
0 2 0
0 2 0
2 2 2
0 2 0
0 2 0
2 2 2
0 2 0
0 2 0
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 0 0 0 0
0 0 4 4 4 4 4 4 0 0
0 0 4 0 0 0 0 0 4 0
0 0 0 4 0 0 0 0 0 4
0 0 0 0 4 0 0 0 0 4
0 0 0 0 4 4 4 4 4 4
0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
7 0 0 0 0 0 0 0 0 0
7 0 0 0 0 0 0 0 0 0
7 0 0 0 0 0 0 0 0 0
8 8 0 0 0 0 0 0 0 0
8 8 0 0 0 0 0 0 0 0
8 6 0 0 0 0 0 0 0 0
0 6 0 0 0 0 0 0 0 0
0 3 3 0 0 0 0 0 0 0
0 3 3 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 4 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 4 4 4 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 4 0 4 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 4 0 4 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 8 8 8 0 2 ... |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
2 0 2
0 0 0
0 0 0
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
2 1 4 2 1 4 2
1 4 2 1 4 2 1
4 2 1 4 2 1 4
2 1 4 2 1 4 2
1 4 2 1 4 2 1
4 2 1 4 2 1 4
2 1 4 2 1 4 2
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0
2 2 2 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 4 4 4 4 4 3 3 0 0 0
2 2 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 4 4 4 4 4 3 3 0 0 0
2 2 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 4 4 4 4 4 3 3 3 0 0
0 0 0 0 0 0 0 0 0 0 2 2 2 0 0 0 0 0 0 8 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 ... |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
0 0 0 2 0 0 0 0 0 0
0 0 0 2 2 0 0 0 0 0
0 8 8 2 2 0 0 0 0 0
0 8 8 0 2 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 2 2 8 2 2 0 2 2 8 2 2 0 2 2 8 2 2 0 0 0 0
0 3 3 8 3 3 0 3 3 8 3 3 0 3 3 8 3 3 0 0 0 0
0 3 3 8 3 3 0 3 3 8 3 3 0 3 3 8 3 3 0 0 0 0
0 8 8 8 8 8 0 8 8 8 8 8 0 8 8 8 8 8 0 0 0 0
0 8 8 8 8 8 0 8 8 8 8 8 0 8 8 8 8 8 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 ... |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 3 3 0
0 0 0 0 0 0 0 0 3
0 0 0 0 0 0 3 0 3
3 3 0 3 3 0 0 0 0
0 0 3 0 0 3 0 0 0
3 0 3 3 0 3 0 0 0
0 0 0 3 3 0 0 0 0
0 0 0 0 0 3 0 0 0
0 0 0 3 0 3 0 0 0
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 4 0 0 4 0 0 4 0 0 4 0 0 4 0 0 4 0 0 4 0 0 4 0 0
0 0 4 0 0 4 0 0 4 0 0 4 0 0 4 0 0 4 0 0 4 0 0 4 0 0
4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
0 0 4 0 0 4 8 8 4 0 0 4 0 0 4 2 2 4 0 0 4 0 0 4 0 0
0 0 4 0 0 4 8 8 4 0 0 4 0 0 4 2 2 4 0 0 4 0 0 4 0 0
4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
0 0 ... |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 3 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0
0 2 2 3 2 2 2 2 2 5 2 2 2 2 2 2 2 0 0 0
0 0 0 3 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0
0 0 0 3 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0
0 0 0 3 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0
0 0 0 3 0 0 0 7 7 5 7 7 7 7 0 0 0 0 ... |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 0 0 0
0 1 0 0 0 0 0 0 0
0 1 0 0 0 2 0 0 0
0 1 0 0 0 2 0 0 0
0 1 0 0 0 2 0 3 0
0 1 0 0 0 2 0 3 0
0 1 0 4 0 2 0 3 0
0 1 0 4 0 2 0 3 0
0 1 0 4 0 2 0 3 0
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 5 2 2 2 5 4 4 4
0 0 0 5 2 2 2 5 4 4 4
0 0 0 5 2 2 2 5 4 4 4
5 5 5 5 5 5 5 5 5 5 5
0 0 0 5 6 6 6 5 3 3 3
0 0 0 5 6 6 6 5 3 3 3
0 0 0 5 6 6 6 5 3 3 3
5 5 5 5 5 5 5 5 5 5 5
0 0 0 5 0 0 0 5 0 0 0
0 0 0 5 0 0 0 5 0 0 0
0 0 0 5 0 0 0 5 0 0 0
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 4 0 3 0 4 0
0 0 0 0 0 0 0 4 3 4 0 0
0 0 0 0 0 0 3 3 4 3 3 0
0 0 0 0 0 0 0 4 3 4 0 0
0 0 0 0 0 0 4 0 3 0 4 0
4 0 3 0 4 0 0 0 0 0 0 0
0 4 3 4 0 0 0 0 0 0 0 0
3 3 4 3 3 0 0 0 0 0 0 0
0 4 3 4 0 0 0 0 0 0 0 0
4 0 3 0 4 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0
0 0 1 1 1 1 0 0 1 4 4 4 1 0 0 1 1 1 1 1 1 0 0 1 4 4 4 4 1 0
0 0 1 4 4 1 1 1 1 4 4 4 1 1 1 1 4 4 4 4 1 1 1 1 4 4 4 4 1 0
0 0 1 4 4 1 0 0 1 4 4 4 1 0 0 1 4 4 4 4 1 0 0 1 4 4 4 4 1 0
0 0 1 1 1 1 0 0 ... |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
2 3 3
4 7 1
1 3 7
4 6 2
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 4 4 4 4 0 0 0 0 0 0 0 2 2 2 0
0 0 4 0 0 4 0 0 4 4 4 0 0 2 0 2 0
0 0 4 4 4 4 4 4 4 0 4 0 0 2 2 2 0
0 0 0 0 4 0 4 0 4 0 4 0 0 2 0 2 0
0 0 0 0 4 4 4 4 4 4 4 0 0 2 0 2 0
0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 2 0
0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0
0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 2 0
0 0 1 1 1 ... |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 3 0 0 0 0 4 0 0 0 0 3 0 0 0 0 4 0 0 0 0 3 0
0 0 0 0 0 3 0 0 0 0 4 0 0 0 0 3 0 0 0 0 4 0 0 0 0 3 0
0 0 0 0 0 3 0 0 0 0 4 0 0 0 0 3 0 0 0 0 4 0 0 0 0 3 0
0 0 0 0 0 3 0 0 0 0 4 0 0 0 0 3 0 0 0 0 4 0 0 0 0 3 0
0 0 0 0 0 3 0 0 0 0 4 0 0 0 0 3 0 0 0 0 4 0 0 0 0 3 0
0 0 0 0 0 3 0 0 0 0 4 0 0 0 0 3 0 0 0 0 4 0 0 ... |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
1 1 1 1 0 1
1 0 1 0 1 1
1 1 0 1 1 0
0 0 0 1 1 1
1 1 1 1 1 1
1 1 1 1 1 1
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 2 0 0 0 0 0
0 0 0 0 0 0 0 0 ... |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 2 2 3 3 3
0 2 0 0 3 3
2 0 2 3 0 0
0 6 6 0 4 0
6 0 6 4 0 4
6 6 0 0 4 0
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
8 9 0 0 0 0 0 0 0 0
2 4 0 0 0 8 8 0 0 0
0 0 0 9 9 9 8 0 0 0
0 0 0 4 9 9 8 0 0 0
0 0 0 4 2 4 0 0 0 0
0 0 0 4 4 2 0 0 0 0
0 0 0 4 2 2 0 0 0 0
0 0 0 8 2 2 0 0 0 0
0 0 0 0 0 2 0 0 0 0
0 0 0 0 0 0 0 0 0 0
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
5 8 5 5 5 5 8 5
8 8 7 7 7 7 8 8
8 7 5 8 8 5 7 8
8 7 5 8 8 5 7 8
8 8 7 7 7 7 8 8
5 8 5 5 5 5 8 5
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 8 0
0 0 0 8
0 8 8 0
0 0 0 0
0 8 0 0
8 8 0 0
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 7 0 0
0 4 0 4 0 7 1 7 0
0 0 2 0 0 0 7 0 0
0 4 0 4 0 0 0 0 0
0 0 0 0 0 8 0 0 0
0 0 0 0 0 0 4 0 4
0 6 0 0 0 0 0 2 0
0 0 0 0 0 0 4 0 4
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
9 5 4
9 5 4
9 5 4
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 1 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 1 0 0 0 1 1 1 0 0 0 0 0 0 0 1 1 1 1 0 0
0 0 0 0 0 1 0 0 0 1 1 1 0 0 0 0 0 0 0 1 1 1 1 0 0
0 0 0 0 1 1 1 0 0 1 1 1 0 1 1 1 1 1 0 1 1 1 1 0 0
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
0 0 0 0 1 1 1 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0 0
0 0 0 0 0 1 0 0 ... |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 ... |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 5 5 5 4 0 0
0 0 0 0 0 0 0 5 0 0 5 0 0
0 0 0 0 0 0 0 5 0 0 5 0 0
0 2 5 5 5 5 5 5 5 5 5 0 0
0 0 0 0 0 0 0 5 0 0 0 0 0
0 0 0 0 0 0 0 5 0 0 0 0 0
0 0 0 0 0 0 0 5 0 0 0 0 0
0 0 0 0 0 0 0 5 0 0 0 0 0
0 0 0 0 0 0 0 5 0 0 0 0 0
0 0 0 0 0 0 0 3 0 0 0 0 0
0 0 ... |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
8 8 8 8 8 8 8 8 8 8 8 8 8 8 8
8 0 0 0 0 0 0 0 0 0 0 0 0 0 8
8 8 8 8 8 8 8 8 8 8 8 8 8 8 8
8 0 0 0 0 0 0 0 0 0 0 0 0 0 8
2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
2 0 0 0 0 0 0 0 0 0 0 0 0 0 2
2 0 0 0 0 0 0 0 0 0 0 0 0 0 2
1 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 0 0 0 0 0 0 0 ... |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 3 3 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 3 3 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 3 3 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 ... |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 3 0 0 0 0 3 0 0 0
8 0 8 0 0 8 0 8 0 0
0 0 8 0 8 0 0 8 0 8
0 0 0 3 0 0 0 0 3 0
8 0 8 0 8 8 0 8 0 8
8 3 8 0 0 8 3 8 0 0
8 3 8 0 0 8 3 8 0 0
8 0 8 0 0 8 0 8 0 0
0 0 8 0 8 0 0 8 0 8
0 0 0 3 0 0 0 0 3 0
8 0 8 0 8 8 0 8 0 8
0 3 0 0 0 0 3 0 0 0
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
0 1 0 4 0 1 0 0 0 0
0 0 2 0 2 0 0 0 0 0
0 4 0 1 0 4 0 0 0 0
0 0 2 0 2 0 0 0 0 0
0 1 0 4 0 1 0 0 0 0
0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
9 9 9 9 9 2 4 7
2 9 9 9 2 4 7 7
4 2 9 2 4 7 7 7
0 4 2 4 7 7 7 7
0 2 4 2 7 7 7 7
2 4 8 4 2 7 7 7
4 8 6 8 4 2 7 7
8 6 3 6 8 4 2 7
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
1 1 1
1 1 1
1 1 1
1 1 1
1 1 1
``` |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
7 7 7 7 7 7 7 7 7 7 7 7 7
7 7 7 7 7 7 7 7 7 7 7 7 7
7 7 7 7 7 7 7 7 7 7 7 7 7
7 7 7 7 7 7 7 7 7 7 7 7 7
7 7 7 7 7 7 7 7 7 7 7 7 7
7 7 7 7 5 7 7 2 7 7 7 7 7
7 7 7 7 5 5 2 2 7 7 7 7 7
7 7 7 7 7 5 2 7 7 7 7 7 7
7 7 7 7 7 7 7 7 7 7 7 7 7
7 7 7 7 7 7 7 7 7 7 7 7 7
7 7 7 7 7 7 7 7 7 7 7 7 7
7 7 7 7 7 7 7 7 7 7 7 7 7
7 7 ... |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 3 0 0 0 0 0 0 0 8 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 3 0 8 0 0 0 0 0
0 0 0 0 0 0 0 5 0 0 0 0 0 0
0 0 0 0 0 0 9 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 9 0 0 0 0 0 0 0 0 0 0
0 0 0 0 ... |
Your task is to infer the rule from the "input" and "output" pairs in the "train" data.
Then, apply that rule to the "test" input to generate the correct "output".
"train": demonstration input/output pairs. It is a list of "pairs" (typically 3 pairs).
"test": test input - your model should predict the output.
A "pair"... | ```
5 0 4 4 4 0 0
5 0 0 8 0 0 0
5 0 0 6 0 0 0
0 0 2 2 0 0 0
0 0 4 4 4 0 0
0 0 0 8 0 0 0
0 0 0 6 0 0 0
0 0 4 4 4 0 0
0 0 0 8 0 0 0
0 0 0 6 0 0 0
``` |
End of preview. Expand in Data Studio
README.md exists but content is empty.
- Downloads last month
- 9